diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_generate.py b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..a239a451f61f99d710a1f62640fce08ea164f264
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_generate.py
@@ -0,0 +1,23 @@
+import pickle
+import pandas as pd
+
+n_target = int(4088)
+with open("/work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf_model.pkl", "rb") as f:
+    model = pickle.load(f)
+syn = model.forge(n=n_target)
+syn = syn.reset_index(drop=True)
+if len(syn) > n_target:
+    syn = syn.iloc[:n_target]
+elif len(syn) < n_target:
+    parts = [syn]
+    tries = 0
+    while sum(len(p) for p in parts) < n_target and tries < 64:
+        tries += 1
+        need = n_target - sum(len(p) for p in parts)
+        chunk = model.forge(n=max(need, 1)).reset_index(drop=True)
+        if len(chunk) == 0:
+            break
+        parts.append(chunk)
+    syn = pd.concat(parts, ignore_index=True).iloc[:n_target]
+syn.to_csv("/work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv", index=False)
+print(f"[ARF] Generated {len(syn)} rows (requested {n_target}) -> /work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv")
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_train.py b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..e897533248bcf376b0e233c24a83ccb016712e31
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/_arf_train.py
@@ -0,0 +1,37 @@
+import pickle
+import numpy as np
+import pandas as pd
+from arfpy import arf
+
+def _sanitize_for_arf(df: pd.DataFrame) -> pd.DataFrame:
+    """缓解 forge 阶段 scipy.stats.truncnorm / 除零：处理 inf、NaN 与极端尾部。"""
+    df = df.replace([np.inf, -np.inf], np.nan)
+    df = df.dropna(axis=1, how="all")
+    for col in df.select_dtypes(include=[np.number]).columns:
+        med = df[col].median()
+        if pd.isna(med):
+            med = 0.0
+        df[col] = df[col].fillna(med)
+        nu = int(df[col].nunique(dropna=True))
+        if nu <= 1:
+            continue
+        lo, hi = df[col].quantile(0.001), df[col].quantile(0.999)
+        if pd.notna(lo) and pd.notna(hi) and lo < hi:
+            df[col] = df[col].clip(lo, hi)
+    return df
+
+df = pd.read_csv("/work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/train.csv")
+df = _sanitize_for_arf(df)
+print(f"[ARF] Training on {len(df)} rows, {len(df.columns)} cols")
+
+model = arf.arf(x=df)
+if hasattr(model, "fit"):
+    model.fit()
+elif hasattr(model, "forde"):
+    model.forde()
+else:
+    raise RuntimeError("arfpy API: no fit() / forde()")
+
+with open("/work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf_model.pkl", "wb") as f:
+    pickle.dump(model, f)
+print(f"[ARF] Model saved -> /work/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf_model.pkl")
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ea36acc7046e851c5bad97be604d18504070ffd2
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5bef5cb3ca3d1d6f827e38f841a31518bd6c09c5318d903c10a6861e9fa08a61
+size 546352
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf_model.pkl b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf_model.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..923d470da177655922a626b8b3ba380bf0e6cfa7
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/arf_model.pkl
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ead2f35ac0c73d397295a8a4a7080b4a4ebf9a4b58fe5b777d13930a91c4dd9a
+size 18331589
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/gen_20260422_060013.log b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/gen_20260422_060013.log
new file mode 100644
index 0000000000000000000000000000000000000000..ad7fe02fb963af534f553412d38692be2928c88c
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/gen_20260422_060013.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbfbdef036085ce71ada368ffab278301c6d149a4f14a6ae26bc81f51e782c6a
+size 2035
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/input_snapshot.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..9b96f8cc51db3866c9fc8aaebf5ddb132876d3cb
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "m7",
+  "model": "arf",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+      "exists": true,
+      "size": 257258,
+      "sha256": "6458faf5495150c1433a95be37eb8d9605954f8474a3d40d9ab9d10adc4cf71e"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+      "exists": true,
+      "size": 32142,
+      "sha256": "bb8674674733508f2c6940b78c07c601654827604862334f9b267e50a83ed9f7"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv",
+      "exists": true,
+      "size": 32328,
+      "sha256": "8b32eb82bd281650cd9f236ef26ec9cd6f02dbaba740770f0e3c4b94a189f3e7"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_profile.json",
+      "exists": true,
+      "size": 5020,
+      "sha256": "ab77a37aa06b0bb854623b7f0caab0c4d4ed05cfce61d9aaf0320c279b20fae5"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_contract_v1.json",
+      "exists": true,
+      "size": 5995,
+      "sha256": "aa9654fbc1dc4029d109adf4117767c5a5c8e90b53bd3f9c698d7b71345cf5b3"
+    }
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c238813dfc1c69038c9a1e618e913e30089a647
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,242 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/public_gate_report.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..44e50731ec49d4928f7a7fdc3843ec48e82b970d
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
+  "dataset_id": "m7",
+  "status": "pass",
+  "checks": [
+    {
+      "check_id": "PG001_csv_parse_ok",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG002_split_header_consistent",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG003_profile_header_match",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG004_missing_token_normalized",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG005_semantic_type_validated",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG006_target_defined_and_valid",
+      "status": "pass"
+    }
+  ],
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cc89b749644d7b2d96da09338ecb343f53ebe8e
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/public_gate/staged_input_manifest.json
@@ -0,0 +1,247 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/runtime_result.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/runtime_result.json
new file mode 100644
index 0000000000000000000000000000000000000000..d8b7a474bf468186ba93908eedace45a847dd5ba
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/runtime_result.json
@@ -0,0 +1,15 @@
+{
+  "dataset_id": "m7",
+  "model": "arf",
+  "run_id": "arf-m7-20260422_055912",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "success",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf-m7-4088-20260422_060013.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/arf_model.pkl"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_report.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..7ba13813452569fe2a47dc789ac11ae914f5b977
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_report.json
@@ -0,0 +1,7 @@
+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/arf/model_input_manifest.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_transforms_applied.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_transforms_applied.json
new file mode 100644
index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/adapter_transforms_applied.json
@@ -0,0 +1 @@
+[]
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/model_input_manifest.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/model_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..66c0e772c15c35197e6ce5afbdd2f67d5a2d6d0c
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/arf/model_input_manifest.json
@@ -0,0 +1,249 @@
+{
+  "dataset_id": "m7",
+  "model": "arf",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/arf/arf-m7-20260422_055912/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/staged_features.json b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/staged_features.json
new file mode 100644
index 0000000000000000000000000000000000000000..e26f1704fb0f87a19ba630fae2eca86da42f4351
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/staged_features.json
@@ -0,0 +1,62 @@
+[
+  {
+    "feature_name": "id",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "gender",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "age",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "hypertension",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "heart_disease",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "ever_married",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "work_type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "Residence_type",
+    "data_type": "categorical",
+    "is_target": true
+  },
+  {
+    "feature_name": "avg_glucose_level",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "bmi",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "smoking_status",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stroke",
+    "data_type": "binary",
+    "is_target": false
+  }
+]
\ No newline at end of file
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/test.csv b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..62356a4507e26f001358cade2a3cfad46c7591ed
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/test.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed44e06410b9395c5c85e238168df0c6952d61bdfe49424863c651ef2b1f4bd8
+size 32934
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/train.csv b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..78eb5ca5098b2cee8ce1f772367c8fdaa201276a
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/train.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f842ac0ec4c47a15867ef35ae0ceede4ef955e556ad5220f982151d22894e25d
+size 262059
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/val.csv b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/val.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2126589cc12e5c467611c829c49647b48fbcbe2
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/staged/public/val.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca541bece6380791dc2c9f7012ec8acbde8a8d270578cc5e031b739f7a761bf8
+size 32704
diff --git a/syntheticSuccess/m7/arf/arf-m7-20260422_055912/train_20260422_055912.log b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/train_20260422_055912.log
new file mode 100644
index 0000000000000000000000000000000000000000..70e56ed4ae922884509614b17f8aeffbb45b203a
--- /dev/null
+++ b/syntheticSuccess/m7/arf/arf-m7-20260422_055912/train_20260422_055912.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c58f16eae31122e7db4279d26f5b157b90d1a49b549771e03e8c87e549521b22
+size 232
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_generate.py b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..30e1bde797f5834a819569d6e4706e7639e5ec1c
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_generate.py
@@ -0,0 +1,75 @@
+
+import pickle
+import warnings
+
+import numpy as np
+import pandas as pd
+from pgmpy.sampling import BayesianModelSampling
+
+warnings.filterwarnings("ignore", category=FutureWarning)
+
+with open("/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl", "rb") as f:
+    bundle = pickle.load(f)
+
+network = bundle["network"]
+inverse = bundle["inverse"]
+cols = bundle["column_order"]
+integer_columns = set(bundle.get("integer_columns") or [])
+full_order = bundle.get("full_column_order") or cols
+const_cols = bundle.get("const_cols") or {}
+
+sampler = BayesianModelSampling(network)
+raw = sampler.forward_sample(size=4088, show_progress=False)
+
+out = pd.DataFrame(index=raw.index)
+rng = np.random.default_rng()
+
+for c in cols:
+    if c in inverse["categorical"]:
+        levels = inverse["categorical"][c]
+        idx = raw[c].astype(int).to_numpy()
+        idx = np.clip(idx, 0, max(0, len(levels) - 1))
+        out[c] = [levels[i] for i in idx]
+    else:
+        edges = np.asarray(inverse["continuous"][c], dtype=float)
+        if edges.size < 2:
+            out[c] = 0.0
+        else:
+            nbin = edges.size - 1
+            res = []
+            for k in raw[c].astype(int).to_numpy():
+                k = int(k)
+                if k < 0:
+                    k = 0
+                if k >= nbin:
+                    k = nbin - 1
+                lo, hi = float(edges[k]), float(edges[k + 1])
+                if hi < lo:
+                    lo, hi = hi, lo
+                v = rng.uniform(lo, hi)
+                if c in integer_columns:
+                    v = int(round(v))
+                res.append(v)
+            out[c] = res
+
+final = pd.DataFrame(index=out.index)
+for c in full_order:
+    if c in const_cols:
+        final[c] = const_cols[c]
+    elif c in out.columns:
+        final[c] = out[c]
+
+dtypes = bundle.get("original_dtypes") or {}
+for c, dts in dtypes.items():
+    if c not in final.columns:
+        continue
+    try:
+        if "int" in dts:
+            final[c] = pd.to_numeric(final[c], errors="coerce").astype("Int64")
+        elif "float" in dts:
+            final[c] = pd.to_numeric(final[c], errors="coerce")
+    except Exception:
+        pass
+
+final.to_csv("/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv", index=False)
+print(f"[BayesNet] Generated 4088 rows -> /work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv")
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_train.py b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..483076da9826d0c090b2e813e9e27480ff4bb82a
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/_bayesnet_train.py
@@ -0,0 +1,93 @@
+
+import json
+import pickle
+import warnings
+
+import numpy as np
+import pandas as pd
+from pgmpy.estimators import TreeSearch
+from pgmpy.models import DiscreteBayesianNetwork
+warnings.filterwarnings("ignore", category=FutureWarning)
+
+with open("/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_coltypes.json", "r", encoding="utf-8") as _f:
+    colmeta = json.load(_f)
+integer_columns = set(colmeta.get("integer_columns") or [])
+
+df = pd.read_csv("/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv")
+df = df.dropna(axis=1, how="all")
+full_column_order = list(df.columns)
+
+const_cols = {}
+for col in list(df.columns):
+    if df[col].nunique(dropna=True) <= 1:
+        const_cols[col] = df[col].iloc[0] if len(df) > 0 else None
+        df = df.drop(columns=[col])
+        print(f"[BayesNet] Dropped zero-variance column '{col}'")
+
+const_path = "/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json")
+with open(const_path, "w", encoding="utf-8") as _f:
+    json.dump({k: str(v) for k, v in const_cols.items()}, _f)
+
+inverse = {"categorical": {}, "continuous": {}}
+enc = pd.DataFrame(index=df.index)
+max_bins = 10
+
+for entry in colmeta["columns"]:
+    name = entry["name"]
+    if name not in df.columns:
+        continue
+    kind = entry["type"]
+    s = df[name]
+    if kind == "categorical":
+        uniques = sorted(s.dropna().unique(), key=lambda x: str(x))
+        mapping = {str(v): i for i, v in enumerate(uniques)}
+        inverse["categorical"][name] = [uniques[i] for i in range(len(uniques))]
+        enc[name] = s.map(lambda x, m=mapping: m.get(str(x), 0)).astype(int)
+    else:
+        s_num = pd.to_numeric(s, errors="coerce")
+        nu = int(s_num.nunique(dropna=True))
+        q = min(max_bins, max(2, nu))
+        if nu < 2:
+            enc[name] = np.zeros(len(s_num), dtype=int)
+            lo, hi = float(s_num.min()), float(s_num.max())
+            inverse["continuous"][name] = [lo, hi]
+        else:
+            try:
+                _, bins = pd.qcut(
+                    s_num, q=q, retbins=True, duplicates="drop"
+                )
+            except Exception:
+                med = float(s_num.median())
+                s2 = s_num.fillna(med)
+                _, bins = pd.qcut(
+                    s2, q=min(q, 3), retbins=True, duplicates="drop"
+                )
+            bins = np.asarray(bins, dtype=float)
+            lab = pd.cut(
+                s_num, bins=bins, labels=False, include_lowest=True
+            )
+            enc[name] = lab.fillna(0).astype(int)
+            inverse["continuous"][name] = bins.tolist()
+
+print(f"[BayesNet] Training on {len(enc)} rows, {len(enc.columns)} cols (encoded)")
+
+dag = TreeSearch(enc).estimate(show_progress=False)
+for col in enc.columns:
+    if col not in dag.nodes():
+        dag.add_node(col)
+        print(f"[BayesNet] Added isolated node to DAG: {col}")
+network = DiscreteBayesianNetwork(dag)
+network.fit(enc)
+
+bundle = {
+    "network": network,
+    "inverse": inverse,
+    "column_order": list(enc.columns),
+    "full_column_order": full_column_order,
+    "integer_columns": list(integer_columns),
+    "original_dtypes": {c: str(df[c].dtype) for c in enc.columns},
+    "const_cols": const_cols,
+}
+with open("/work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl", "wb") as _f:
+    pickle.dump(bundle, _f)
+print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl")
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv
new file mode 100644
index 0000000000000000000000000000000000000000..df6c17750aaa7fa0c66795f80949bc07c9acf115
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2e5c21f598d833656dad80ad005d7886a7d0535cf6a176db88712036d65114f
+size 471242
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_coltypes.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_coltypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..a76104d60a8e8b3ee4b869e9115643f20baf2cac
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_coltypes.json
@@ -0,0 +1,53 @@
+{
+  "columns": [
+    {
+      "name": "id",
+      "type": "continuous"
+    },
+    {
+      "name": "gender",
+      "type": "categorical"
+    },
+    {
+      "name": "age",
+      "type": "continuous"
+    },
+    {
+      "name": "hypertension",
+      "type": "categorical"
+    },
+    {
+      "name": "heart_disease",
+      "type": "categorical"
+    },
+    {
+      "name": "ever_married",
+      "type": "categorical"
+    },
+    {
+      "name": "work_type",
+      "type": "categorical"
+    },
+    {
+      "name": "Residence_type",
+      "type": "categorical"
+    },
+    {
+      "name": "avg_glucose_level",
+      "type": "continuous"
+    },
+    {
+      "name": "bmi",
+      "type": "continuous"
+    },
+    {
+      "name": "smoking_status",
+      "type": "categorical"
+    },
+    {
+      "name": "stroke",
+      "type": "categorical"
+    }
+  ],
+  "integer_columns": []
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..085bbfe2d363ea173e8b13515dd35bc6aeca4b2a
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b0bdcb832b623c4da609bdd6797732e4cc4fe3f72c6f0381b10e975e5d251c0a
+size 11519
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/const_cols.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/const_cols.json
new file mode 100644
index 0000000000000000000000000000000000000000..9e26dfeeb6e641a33dae4961196235bdb965b21b
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/const_cols.json
@@ -0,0 +1 @@
+{}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/gen_20260420_035257.log b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/gen_20260420_035257.log
new file mode 100644
index 0000000000000000000000000000000000000000..689c25998e4773c7acdce7e685459092a244993e
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/gen_20260420_035257.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0899e478ccf5e9c9b1dc6f8963f6a62360aab8b45b5b4cdd51ab0b7737b4bd8
+size 1134
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/input_snapshot.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..634440684cc809a8e51c4538eea433c0b84dcc6a
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "m7",
+  "model": "bayesnet",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+      "exists": true,
+      "size": 257258,
+      "sha256": "6458faf5495150c1433a95be37eb8d9605954f8474a3d40d9ab9d10adc4cf71e"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+      "exists": true,
+      "size": 32142,
+      "sha256": "bb8674674733508f2c6940b78c07c601654827604862334f9b267e50a83ed9f7"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv",
+      "exists": true,
+      "size": 32328,
+      "sha256": "8b32eb82bd281650cd9f236ef26ec9cd6f02dbaba740770f0e3c4b94a189f3e7"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_profile.json",
+      "exists": true,
+      "size": 5020,
+      "sha256": "ab77a37aa06b0bb854623b7f0caab0c4d4ed05cfce61d9aaf0320c279b20fae5"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_contract_v1.json",
+      "exists": true,
+      "size": 5995,
+      "sha256": "aa9654fbc1dc4029d109adf4117767c5a5c8e90b53bd3f9c698d7b71345cf5b3"
+    }
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c238813dfc1c69038c9a1e618e913e30089a647
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,242 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/public_gate_report.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..44e50731ec49d4928f7a7fdc3843ec48e82b970d
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
+  "dataset_id": "m7",
+  "status": "pass",
+  "checks": [
+    {
+      "check_id": "PG001_csv_parse_ok",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG002_split_header_consistent",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG003_profile_header_match",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG004_missing_token_normalized",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG005_semantic_type_validated",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG006_target_defined_and_valid",
+      "status": "pass"
+    }
+  ],
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..b0e9b9ec63834956c89a7b79da3b5c8d8c660739
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/staged_input_manifest.json
@@ -0,0 +1,247 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/runtime_result.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/runtime_result.json
new file mode 100644
index 0000000000000000000000000000000000000000..43a050605f638a4bed70672ad96ba84256b0a414
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/runtime_result.json
@@ -0,0 +1,15 @@
+{
+  "dataset_id": "m7",
+  "model": "bayesnet",
+  "run_id": "bayesnet-m7-20260420_035052",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "success",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet-m7-4088-20260420_035257.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/bayesnet_model.pkl"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_report.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..bdec670271d663c00072c4c5f3fecd68bfbc5c64
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_report.json
@@ -0,0 +1,7 @@
+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/model_input_manifest.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_transforms_applied.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_transforms_applied.json
new file mode 100644
index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/adapter_transforms_applied.json
@@ -0,0 +1 @@
+[]
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/model_input_manifest.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/model_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..c470a07f52a2e8b2c0b64ccb75525347a481e944
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/bayesnet/model_input_manifest.json
@@ -0,0 +1,249 @@
+{
+  "dataset_id": "m7",
+  "model": "bayesnet",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/bayesnet/bayesnet-m7-20260420_035052/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/staged_features.json b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/staged_features.json
new file mode 100644
index 0000000000000000000000000000000000000000..e26f1704fb0f87a19ba630fae2eca86da42f4351
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/staged_features.json
@@ -0,0 +1,62 @@
+[
+  {
+    "feature_name": "id",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "gender",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "age",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "hypertension",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "heart_disease",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "ever_married",
+    "data_type": "binary",
+    "is_target": false
+  },
+  {
+    "feature_name": "work_type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "Residence_type",
+    "data_type": "categorical",
+    "is_target": true
+  },
+  {
+    "feature_name": "avg_glucose_level",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "bmi",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "smoking_status",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stroke",
+    "data_type": "binary",
+    "is_target": false
+  }
+]
\ No newline at end of file
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/test.csv b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..62356a4507e26f001358cade2a3cfad46c7591ed
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/test.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed44e06410b9395c5c85e238168df0c6952d61bdfe49424863c651ef2b1f4bd8
+size 32934
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..78eb5ca5098b2cee8ce1f772367c8fdaa201276a
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/train.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f842ac0ec4c47a15867ef35ae0ceede4ef955e556ad5220f982151d22894e25d
+size 262059
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/val.csv b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/val.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2126589cc12e5c467611c829c49647b48fbcbe2
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/staged/public/val.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca541bece6380791dc2c9f7012ec8acbde8a8d270578cc5e031b739f7a761bf8
+size 32704
diff --git a/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/train_20260420_035053.log b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/train_20260420_035053.log
new file mode 100644
index 0000000000000000000000000000000000000000..b7b662f22f68583586f5b1c2d521c7d6e496a1ad
--- /dev/null
+++ b/syntheticSuccess/m7/bayesnet/bayesnet-m7-20260420_035052/train_20260420_035053.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ded2907debedaf80869e394afc9cdbdf5d0f959d8cb6aa37b67fe8d901338fb
+size 1160
diff --git a/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/_ctgan_generate.py b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/_ctgan_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..27504ddb86e6984b49226bd60e57561ced507396
--- /dev/null
+++ b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/_ctgan_generate.py
@@ -0,0 +1,18 @@
+import sys
+sys.path.insert(0, "/work")
+from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix
+apply_ctgan_inverse_fix()
+import pandas as pd
+from ctgan.synthesizers.ctgan import CTGAN
+model = CTGAN.load("/work/output-SpecializedModels/m7/ctgan/ctgan-m7-20260422_031259/models_300epochs/ctgan_300epochs.pt")
+total = 4088
+chunk = min(50000, total) if total > 50000 else total
+parts = []
+left = total
+while left > 0:
+    take = min(chunk, left)
+    parts.append(model.sample(take))
+    left -= take
+sampled = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0]
+sampled.to_csv("/work/output-SpecializedModels/m7/ctgan/ctgan-m7-20260422_031259/ctgan-m7-4088-20260422_031701.csv", index=False)
+print("[CTGAN] Generated", total, "rows in", len(parts), "chunks ->", "/work/output-SpecializedModels/m7/ctgan/ctgan-m7-20260422_031259/ctgan-m7-4088-20260422_031701.csv")
\ No newline at end of file
diff --git a/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan-m7-4088-20260422_031701.csv b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan-m7-4088-20260422_031701.csv
new file mode 100644
index 0000000000000000000000000000000000000000..03021c091ee9035841a909cb89251e9b7941662d
--- /dev/null
+++ b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan-m7-4088-20260422_031701.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1a571fd61abd1274a28afa0afcb2ee0fb10939f6b880b59ea9de73ac8d6c501e
+size 427328
diff --git a/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_metadata.json b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..401efafec49762d3e443188f4f45914377273a24
--- /dev/null
+++ b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_metadata.json
@@ -0,0 +1,52 @@
+{
+  "columns": [
+    {
+      "name": "id",
+      "type": "continuous"
+    },
+    {
+      "name": "gender",
+      "type": "categorical"
+    },
+    {
+      "name": "age",
+      "type": "continuous"
+    },
+    {
+      "name": "hypertension",
+      "type": "categorical"
+    },
+    {
+      "name": "heart_disease",
+      "type": "categorical"
+    },
+    {
+      "name": "ever_married",
+      "type": "categorical"
+    },
+    {
+      "name": "work_type",
+      "type": "categorical"
+    },
+    {
+      "name": "Residence_type",
+      "type": "categorical"
+    },
+    {
+      "name": "avg_glucose_level",
+      "type": "continuous"
+    },
+    {
+      "name": "bmi",
+      "type": "continuous"
+    },
+    {
+      "name": "smoking_status",
+      "type": "categorical"
+    },
+    {
+      "name": "stroke",
+      "type": "categorical"
+    }
+  ]
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_train_continuous_imputed.csv b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_train_continuous_imputed.csv
new file mode 100644
index 0000000000000000000000000000000000000000..32d9774716b9e7b55e898959e468787a23bd9ed9
--- /dev/null
+++ b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/ctgan_train_continuous_imputed.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/staged/public/staged_features.json b/syntheticSuccess/m7/ctgan/ctgan-m7-20260422_031259/staged/public/staged_features.json
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diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/public_gate/public_gate_report.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/public_gate/public_gate_report.json
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\ No newline at end of file
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/public_gate/staged_input_manifest.json
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diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/realtabformer_features.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/realtabformer_features.json
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/realtabformer_features.json
@@ -0,0 +1,62 @@
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diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/staged_features.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/staged_features.json
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diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/test.csv b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/test.csv
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index 0000000000000000000000000000000000000000..62356a4507e26f001358cade2a3cfad46c7591ed
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/test.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed44e06410b9395c5c85e238168df0c6952d61bdfe49424863c651ef2b1f4bd8
+size 32934
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/train.csv b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..78eb5ca5098b2cee8ce1f772367c8fdaa201276a
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/train.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f842ac0ec4c47a15867ef35ae0ceede4ef955e556ad5220f982151d22894e25d
+size 262059
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/val.csv b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/val.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2126589cc12e5c467611c829c49647b48fbcbe2
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/public/val.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca541bece6380791dc2c9f7012ec8acbde8a8d270578cc5e031b739f7a761bf8
+size 32704
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_report.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..d4c136c237fe5e68911bb28064f63b28f4aa065f
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_report.json
@@ -0,0 +1,7 @@
+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/model_input_manifest.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_transforms_applied.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_transforms_applied.json
new file mode 100644
index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/adapter_transforms_applied.json
@@ -0,0 +1 @@
+[]
\ No newline at end of file
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/model_input_manifest.json b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/model_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..6aea95b9bf7091ac4960a47c1e740576c73db61c
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/staged/realtabformer/model_input_manifest.json
@@ -0,0 +1,249 @@
+{
+  "dataset_id": "m7",
+  "model": "realtabformer",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/realtabformer/rtf-m7-20260330_020623/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/train_20260330_020623.log b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/train_20260330_020623.log
new file mode 100644
index 0000000000000000000000000000000000000000..fcdaa5729b96342194169e146f8b714ef8ffaee2
--- /dev/null
+++ b/syntheticSuccess/m7/realtabformer/rtf-m7-20260330_020623/train_20260330_020623.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09ccb0230be65bbd8b1a17063ae01a0889340c1e32eca8cf8dca2324528f1196
+size 907257
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_sample.py b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fcf76d5e89367728e0b231972dd9f328de74701
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_sample.py
@@ -0,0 +1,67 @@
+import os, sys, subprocess, json
+import numpy as np
+import pandas as pd
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Reuse the compat wrapper (patches collections.Sequence for skorch)
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+if not os.path.exists(wrapper):
+    with open(wrapper, "w") as f:
+        f.write(
+            "import collections, collections.abc\n"
+            "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+            "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+            "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+            "import sys, runpy\n"
+            "sys.argv = sys.argv[1:]\n"
+            "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+        )
+
+print(f"[TabDDPM] Sampling 4088 rows")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/config_sample_20260424_034049.toml",
+     "--sample"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+
+# 将 .npy 输出转为 CSV
+work_dir = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725"
+info_path = os.path.join(work_dir, "data", "info.json")
+with open(info_path) as f:
+    info = json.load(f)
+
+output_dir = os.path.join(work_dir, "output")
+col_names = info.get("column_names", [])
+
+parts = []
+x_num_path = os.path.join(output_dir, "X_num_train.npy")
+x_cat_path = os.path.join(output_dir, "X_cat_train.npy")
+y_path = os.path.join(output_dir, "y_train.npy")
+
+if os.path.exists(x_num_path):
+    parts.append(np.load(x_num_path, allow_pickle=True))
+if os.path.exists(x_cat_path):
+    parts.append(np.load(x_cat_path, allow_pickle=True).astype(float))
+if os.path.exists(y_path):
+    y = np.load(y_path, allow_pickle=True)
+    parts.append(y.reshape(-1, 1) if y.ndim == 1 else y)
+
+if parts:
+    combined = np.concatenate(parts, axis=1)
+    if col_names and len(col_names) == combined.shape[1]:
+        df = pd.DataFrame(combined, columns=col_names)
+    else:
+        df = pd.DataFrame(combined)
+    df.to_csv("/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/tabddpm-m7-4088-20260424_034049.csv", index=False)
+    print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/tabddpm-m7-4088-20260424_034049.csv")
+else:
+    print("[TabDDPM] WARNING: No output .npy files found")
+    sys.exit(1)
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_train.py b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce8e504ea3f558f5479c6b1f657fd5538a31586e
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config.toml b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..078cce3c915d1a434460375204750cd92e68cf12
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 4
+device = "cuda:0"
+
+[model_params]
+d_in = 11
+num_classes = 2
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config_sample_20260424_034049.toml b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config_sample_20260424_034049.toml
new file mode 100644
index 0000000000000000000000000000000000000000..3f4de2bfbade1439654e667a8baa11a9a57443d6
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/config_sample_20260424_034049.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 4
+device = "cuda:0"
+
+[model_params]
+d_in = 11
+num_classes = 2
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 4088
+batch_size = 1000
+seed = 0
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_cat_train.npy b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_cat_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..22e66cc024d9b5074441448f37a305cc02e2220a
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_cat_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77eabddf51b42a34df2c46915bd3f7823d70992a87a7b4348f0d965ea2758720
+size 229056
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_num_train.npy b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_num_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..645d0375ebd1f8704052198fc7650cc89a19301f
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/X_num_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca67a733724ef0e1fc312d8790da6665adfa29b99d2264bdebbfe342a450e65d
+size 65536
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/info.json b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/data/info.json
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+parent_dir = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/m7/tabddpm/tabddpm-m7-20260424_033725/data"
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+[model_params]
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+[model_params.rtdl_params]
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+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
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+lr = 0.001
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+
+[train.T]
+seed = 0
+normalization = "quantile"
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+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
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+[sample]
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+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/public_gate/staged_input_manifest.json
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+size 411031
diff --git a/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/train_20260424_033725.log b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/train_20260424_033725.log
new file mode 100644
index 0000000000000000000000000000000000000000..a6d55fd16738c8f518111a2b42f29b3b6b745caf
--- /dev/null
+++ b/syntheticSuccess/m7/tabddpm/tabddpm-m7-20260424_033725/train_20260424_033725.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 845
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_sample.py b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..85007d0d5f1eabe70f8a4f6d1f91e0e2fa5c592d
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_sample.py
@@ -0,0 +1,39 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807"
+dataname = "tabsyn_m7"
+output_csv = "/work/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260502_050021.csv"
+tabsyn_root = "/workspace/tabsyn"
+
+assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}"
+
+old = os.environ.get("PYTHONPATH", "")
+os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "")
+sys.path.insert(0, tabsyn_root)
+
+os.chdir(tabsyn_root)
+
+# Ensure data symlink exists
+data_link = os.path.join(tabsyn_root, "data", dataname)
+data_src = os.path.join(work_dir, "data", dataname)
+os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True)
+if os.path.exists(data_link):
+    os.remove(data_link)
+os.symlink(data_src, data_link)
+
+print(f"[TabSyn] Sampling 4088 rows")
+env = os.environ.copy()
+env.setdefault("TABSYN_RESUME", "1")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "sample",
+     "--method", "tabsyn",
+     "--gpu", "0",
+     "--save_path", output_csv],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print(f"[TabSyn] Saved -> {output_csv}")
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_train.py b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..4012463b969e78b84763f5db452f5ebb10985ca8
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/_tabsyn_train.py
@@ -0,0 +1,62 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807"
+dataname = "tabsyn_m7"
+tabsyn_root = "/workspace/tabsyn"
+
+assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}"
+
+old = os.environ.get("PYTHONPATH", "")
+os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "")
+sys.path.insert(0, tabsyn_root)
+
+os.chdir(tabsyn_root)
+
+# Symlink data dir into TabSyn data/
+data_link = os.path.join(tabsyn_root, "data", dataname)
+data_src = os.path.join(work_dir, "data", dataname)
+os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True)
+if os.path.exists(data_link):
+    os.remove(data_link)
+os.symlink(data_src, data_link)
+
+env = os.environ.copy()
+env.setdefault("TABSYN_RESUME", "1")
+_te = None
+if _te is not None:
+    env["TABSYN_VAE_EPOCHS"] = str(_te)
+    env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2))
+
+# Data preprocessing is done on the host side (_prepare_data_dir)
+# which creates .npy files, train/test CSVs, and info.json
+
+# Step 1: Train VAE (produces latent embeddings)
+print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "vae",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] VAE training failed")
+    sys.exit(ret.returncode)
+
+# Step 2: Train diffusion model on latent space
+print(f"[TabSyn] Step 2/2: Training diffusion model")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "tabsyn",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] Diffusion training failed")
+    sys.exit(ret.returncode)
+print("[TabSyn] Training complete (VAE + Diffusion)")
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_test.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..2c465a4fcac15fcbb8237d6052f3707bc194127b
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_test.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:101c28e9b959017c5587c968cbe4dc4c4fc08010a402f6293f50cd5963679637
+size 28744
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_train.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..cb2b53ba05ccfe0d6951f94d5946c0c4d3a65033
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_cat_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e0d7cb00f7a8b441bd78306523d6e82237faed08401812009284b18049995f4
+size 257672
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_test.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..b748ffbc5ee19983f03bb4e1b6967a4ec822f324
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_test.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 8304
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_train.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..b31c6b0067a45ce9445eb0cb0995b9c343c50ef1
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/X_num_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 73712
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/info.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/info.json
new file mode 100644
index 0000000000000000000000000000000000000000..2774c093aeec1505116dca4806f5604523caa737
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/info.json
@@ -0,0 +1,132 @@
+{
+  "name": "tabsyn_m7",
+  "task_type": "multiclass",
+  "n_num_features": 4,
+  "n_cat_features": 7,
+  "train_size": 4599,
+  "num_col_idx": [
+    0,
+    2,
+    8,
+    9
+  ],
+  "cat_col_idx": [
+    1,
+    3,
+    4,
+    5,
+    6,
+    10,
+    11
+  ],
+  "target_col_idx": [
+    7
+  ],
+  "column_names": [
+    "id",
+    "gender",
+    "age",
+    "hypertension",
+    "heart_disease",
+    "ever_married",
+    "work_type",
+    "Residence_type",
+    "avg_glucose_level",
+    "bmi",
+    "smoking_status",
+    "stroke"
+  ],
+  "train_num": 4599,
+  "test_num": 511,
+  "header": 0,
+  "file_type": "csv",
+  "data_path": "data/tabsyn_m7/train.csv",
+  "test_path": null,
+  "idx_mapping": {
+    "0": 0,
+    "1": 4,
+    "2": 1,
+    "3": 5,
+    "4": 6,
+    "5": 7,
+    "6": 8,
+    "7": 11,
+    "8": 2,
+    "9": 3,
+    "10": 9,
+    "11": 10
+  },
+  "inverse_idx_mapping": {
+    "0": 0,
+    "4": 1,
+    "1": 2,
+    "5": 3,
+    "6": 4,
+    "7": 5,
+    "8": 6,
+    "11": 7,
+    "2": 8,
+    "3": 9,
+    "9": 10,
+    "10": 11
+  },
+  "idx_name_mapping": {
+    "0": "id",
+    "1": "gender",
+    "2": "age",
+    "3": "hypertension",
+    "4": "heart_disease",
+    "5": "ever_married",
+    "6": "work_type",
+    "7": "Residence_type",
+    "8": "avg_glucose_level",
+    "9": "bmi",
+    "10": "smoking_status",
+    "11": "stroke"
+  },
+  "n_classes": 2,
+  "metadata": {
+    "columns": {
+      "0": {
+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
+      "2": {
+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
+      "8": {
+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
+      "9": {
+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
+      "1": {
+        "sdtype": "categorical"
+      },
+      "3": {
+        "sdtype": "categorical"
+      },
+      "4": {
+        "sdtype": "categorical"
+      },
+      "5": {
+        "sdtype": "categorical"
+      },
+      "6": {
+        "sdtype": "categorical"
+      },
+      "10": {
+        "sdtype": "categorical"
+      },
+      "11": {
+        "sdtype": "categorical"
+      },
+      "7": {
+        "sdtype": "categorical"
+      }
+    }
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/test.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2db20df22d87603fc9c5c41abe31648b3a53da43
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/test.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 19502
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/train.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/train.csv
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/train.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 174411
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_test.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_test.npy
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_test.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ef7f5752d14bfbe92acfae378c56c8267aaf6829a44a4d18481a74314832c40
+size 4216
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_train.npy b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_train.npy
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/data/tabsyn_m7/y_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 36920
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/gen_20260420_230908.log b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/gen_20260420_230908.log
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--- /dev/null
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@@ -0,0 +1,3 @@
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+size 665
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/gen_20260502_050021.log b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/gen_20260502_050021.log
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/gen_20260502_050021.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 930
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/input_snapshot.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c02c0b29c28b296641d1ea25f4d0512df166ad
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "m7",
+  "model": "tabsyn",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+      "exists": true,
+      "size": 257258,
+      "sha256": "6458faf5495150c1433a95be37eb8d9605954f8474a3d40d9ab9d10adc4cf71e"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+      "exists": true,
+      "size": 32142,
+      "sha256": "bb8674674733508f2c6940b78c07c601654827604862334f9b267e50a83ed9f7"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv",
+      "exists": true,
+      "size": 32328,
+      "sha256": "8b32eb82bd281650cd9f236ef26ec9cd6f02dbaba740770f0e3c4b94a189f3e7"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_profile.json",
+      "exists": true,
+      "size": 5020,
+      "sha256": "ab77a37aa06b0bb854623b7f0caab0c4d4ed05cfce61d9aaf0320c279b20fae5"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_contract_v1.json",
+      "exists": true,
+      "size": 5995,
+      "sha256": "aa9654fbc1dc4029d109adf4117767c5a5c8e90b53bd3f9c698d7b71345cf5b3"
+    }
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c238813dfc1c69038c9a1e618e913e30089a647
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,242 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
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+      "nullable": false,
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diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/public_gate_report.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/public_gate_report.json
new file mode 100644
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+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/staged_input_manifest.json
new file mode 100644
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diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/runtime_result.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/runtime_result.json
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--- /dev/null
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@@ -0,0 +1,26 @@
+{
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+  },
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+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/staged_features.json b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/staged_features.json
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+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/staged_features.json
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diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/test.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/test.csv
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+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.039873,
+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tabsyn/tabsyn-m7-20260420_221807/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/real.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/real.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c521227c35dc6e0a6801491f5ccaec7abded5f60
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/real.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a01c57cbca2c28b41451dceab4e171d9a5d72447394b6e7fdba7da3d804f6a3d
+size 174411
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/test.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2db20df22d87603fc9c5c41abe31648b3a53da43
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/synthetic/tabsyn_m7/test.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:083da84806e8170ef5e7e3360fa2b1f4fbdef4dd1d5e7147aa29fe4e262e68a7
+size 19502
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260420_230908.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260420_230908.csv
new file mode 100644
index 0000000000000000000000000000000000000000..712200719db4e1ce832637702cfc9509f2c432dc
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260420_230908.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ac41bc94bd5013cae7872425ca204a4d2bdcd94493f570b2e26b2bdfdc018bd6
+size 241463
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260502_050021.csv b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260502_050021.csv
new file mode 100644
index 0000000000000000000000000000000000000000..755620d85ba247044328bf887388bba233c2f891
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/tabsyn-m7-4088-20260502_050021.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6aefeea040fcf30731651506141b0ba4b03c5e478a57e0426d77daf64249e609
+size 241237
diff --git a/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/train_20260420_221807.log b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/train_20260420_221807.log
new file mode 100644
index 0000000000000000000000000000000000000000..b4264c589381479b1cd6b1c4ce2fa6573c6dc062
--- /dev/null
+++ b/syntheticSuccess/m7/tabsyn/tabsyn-m7-20260420_221807/train_20260420_221807.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a1c691ce2b51a41eb0c39e7e8b05f5c807400827f0e13ee2f55d22207a924b1
+size 2703767
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_generate.py b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..b47a8158e12d9e33c5f7d7620dcf32c97f0cc177
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_generate.py
@@ -0,0 +1,18 @@
+import sys
+sys.path.insert(0, "/work")
+from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix
+apply_ctgan_inverse_fix()
+import pandas as pd
+from ctgan.synthesizers.tvae import TVAE
+model = TVAE.load("/work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/models_300epochs/tvae_300epochs.pt")
+total = 4088
+chunk = min(50000, total) if total > 50000 else total
+parts = []
+left = total
+while left > 0:
+    take = min(chunk, left)
+    parts.append(model.sample(take))
+    left -= take
+samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0]
+samples.to_csv("/work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv", index=False)
+print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv")
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_train.py b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..cddaa52b27a6b0049ee03111a5b7d7eb0555eaa7
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/_tvae_train.py
@@ -0,0 +1,16 @@
+import json, sys
+import pandas as pd
+from ctgan.data import read_csv
+from ctgan.synthesizers.tvae import TVAE
+
+csv_path = "/work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/train.csv"
+meta_path = "/work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/tvae_metadata.json"
+save_path = "/work/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/models_300epochs/tvae_300epochs.pt"
+epochs = 300
+
+data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None)
+print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}")
+model = TVAE(epochs=epochs, batch_size=500)
+model.fit(data, discrete_columns)
+model.save(save_path)
+print(f"[TVAE] Model saved -> {save_path}")
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260328_053025.log b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260328_053025.log
new file mode 100644
index 0000000000000000000000000000000000000000..d3aaa5f5c6e157299fe7b1a0e4978d0d1af32070
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260328_053025.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5272ee30c7e7727c9664f3e35db552f827506f541c1d2964546492b7c57bbc4e
+size 1360
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260419_065547.log b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260419_065547.log
new file mode 100644
index 0000000000000000000000000000000000000000..4cf25f28a513f26149af2d583fa8e29a6b91b3f9
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260419_065547.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87523d404f989bb911b99802573e9d97ced8306a1790a3f6a4f170325780de04
+size 2094
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260420_024605.log b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260420_024605.log
new file mode 100644
index 0000000000000000000000000000000000000000..e5f78d0885d34c0a118f8193d30c8c6d0c5132da
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/gen_20260420_024605.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a84d41fd5a16655b09854131fc6cac8d72b1430f920d0116343a988bcae4f45
+size 539
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/input_snapshot.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..706290f79f05bbc57f53e6dba2728f8113c4b129
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "m7",
+  "model": "tvae",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-train.csv",
+      "exists": true,
+      "size": 257258,
+      "sha256": "6458faf5495150c1433a95be37eb8d9605954f8474a3d40d9ab9d10adc4cf71e"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+      "exists": true,
+      "size": 32142,
+      "sha256": "bb8674674733508f2c6940b78c07c601654827604862334f9b267e50a83ed9f7"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv",
+      "exists": true,
+      "size": 32328,
+      "sha256": "8b32eb82bd281650cd9f236ef26ec9cd6f02dbaba740770f0e3c4b94a189f3e7"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_profile.json",
+      "exists": true,
+      "size": 5020,
+      "sha256": "ab77a37aa06b0bb854623b7f0caab0c4d4ed05cfce61d9aaf0320c279b20fae5"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m7/m7-dataset_contract_v1.json",
+      "exists": true,
+      "size": 5995,
+      "sha256": "aa9654fbc1dc4029d109adf4117767c5a5c8e90b53bd3f9c698d7b71345cf5b3"
+    }
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/train_20260328_052614.log b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/train_20260328_052614.log
new file mode 100644
index 0000000000000000000000000000000000000000..2cd5817858180b64d06af71a1fdc83fccf716b4a
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/train_20260328_052614.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3948f226903cada55a42b1dcfb88110f8149076880ce3bff45cb7366395e3ee
+size 170
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/tvae_300epochs.pt b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/tvae_300epochs.pt
new file mode 100644
index 0000000000000000000000000000000000000000..243db0387079a5878467ca69a15de7eccb081f3b
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/models_300epochs/tvae_300epochs.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 565548
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c238813dfc1c69038c9a1e618e913e30089a647
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,242 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4088,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "35296",
+          "36710",
+          "32733",
+          "1077",
+          "13223"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Female",
+          "Male"
+        ]
+      }
+    },
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 104,
+        "unique_ratio": 0.02544,
+        "example_values": [
+          "58",
+          "64",
+          "28",
+          "77",
+          "53"
+        ]
+      }
+    },
+    {
+      "name": "hypertension",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "heart_disease",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "ever_married",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Yes",
+          "No"
+        ]
+      }
+    },
+    {
+      "name": "work_type",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.001223,
+        "example_values": [
+          "Private",
+          "Govt_job",
+          "Self-employed",
+          "children",
+          "Never_worked"
+        ]
+      }
+    },
+    {
+      "name": "Residence_type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "Rural",
+          "Urban"
+        ]
+      }
+    },
+    {
+      "name": "avg_glucose_level",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3337,
+        "unique_ratio": 0.816292,
+        "example_values": [
+          "100.42",
+          "62.21",
+          "106.68",
+          "106.03",
+          "86.39"
+        ]
+      }
+    },
+    {
+      "name": "bmi",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/public_gate_report.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..44e50731ec49d4928f7a7fdc3843ec48e82b970d
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
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+  "status": "pass",
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+      "status": "pass"
+    },
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+      "status": "pass"
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+      "status": "pass"
+    },
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+      "status": "pass"
+    }
+  ],
+  "target_column": "Residence_type",
+  "task_type": "classification",
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+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m7/m7-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/staged_input_manifest.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/staged_input_manifest.json
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/public_gate/staged_input_manifest.json
@@ -0,0 +1,247 @@
+{
+  "dataset_id": "m7",
+  "target_column": "Residence_type",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/val.csv",
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diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/runtime_result.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/runtime_result.json
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/runtime_result.json
@@ -0,0 +1,14 @@
+{
+  "dataset_id": "m7",
+  "model": "tvae",
+  "run_id": "tvae-m7-20260328_052614",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "skipped",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv"
+  }
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/staged/public/staged_features.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/staged/public/staged_features.json
new file mode 100644
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--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/staged/public/staged_features.json
@@ -0,0 +1,62 @@
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diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/staged/public/test.csv b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/staged/public/test.csv
new file mode 100644
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+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": true,
+      "missing_tokens": [
+        "N/A"
+      ],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 396,
+        "unique_ratio": 0.100892,
+        "example_values": [
+          "39.5",
+          "28.3",
+          "29.3",
+          "30.2",
+          "48.9"
+        ]
+      }
+    },
+    {
+      "name": "smoking_status",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000978,
+        "example_values": [
+          "smokes",
+          "Unknown",
+          "never smoked",
+          "formerly smoked"
+        ]
+      }
+    },
+    {
+      "name": "stroke",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000489,
+        "example_values": [
+          "0",
+          "1"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m7/tvae/tvae-m7-20260328_052614/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9f898450a64959517a47d94e1dcf9ad6adcb4abd
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae-m7-4088-20260420_024605.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7ff8a44ab36e223fbad11ed0ddc52911674b7d5c7493f4704db0139f9fb72d14
+size 390785
diff --git a/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae_metadata.json b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae_metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..401efafec49762d3e443188f4f45914377273a24
--- /dev/null
+++ b/syntheticSuccess/m7/tvae/tvae-m7-20260328_052614/tvae_metadata.json
@@ -0,0 +1,52 @@
+{
+  "columns": [
+    {
+      "name": "id",
+      "type": "continuous"
+    },
+    {
+      "name": "gender",
+      "type": "categorical"
+    },
+    {
+      "name": "age",
+      "type": "continuous"
+    },
+    {
+      "name": "hypertension",
+      "type": "categorical"
+    },
+    {
+      "name": "heart_disease",
+      "type": "categorical"
+    },
+    {
+      "name": "ever_married",
+      "type": "categorical"
+    },
+    {
+      "name": "work_type",
+      "type": "categorical"
+    },
+    {
+      "name": "Residence_type",
+      "type": "categorical"
+    },
+    {
+      "name": "avg_glucose_level",
+      "type": "continuous"
+    },
+    {
+      "name": "bmi",
+      "type": "continuous"
+    },
+    {
+      "name": "smoking_status",
+      "type": "categorical"
+    },
+    {
+      "name": "stroke",
+      "type": "categorical"
+    }
+  ]
+}
\ No newline at end of file