AM13_MeltpoolNet / README.md
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AM13_MeltpoolNet: T-AM2 unified SFT (viewer-friendly row groups)
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---
tags:
- smart-manufacturing
- additive-manufacturing
- sft
license: other
pretty_name: AM13_MeltpoolNet
extra_gated_fields:
Name: text
Affiliation: text
Intended use: text
extra_gated_prompt: >-
This dataset is released for **research use** and access is reviewed and granted
**manually** by the maintainers. Licensing of the underlying source is NOT yet cleared
(see the card). Please state your name, affiliation, and intended use.
---
# AM13_MeltpoolNet
Unit-normalized process/material inputs -> source-native 5-way melt-pool mode classification. Tabular. Category **C**, task **T-AM2**, in the unified Smart-Manufacturing SFT schema.
## Records
**1,236** records (train=1,236). Model input: tabular — no image.
## Unified SFT schema (7 fields)
| field | type | meaning |
|---|---|---|
| `query` | str | the question / instruction (model input) |
| `image` | Image \| null | the INPUT image (bytes embedded) — null for tabular records |
| `annot` | str | the answer — for this dataset: a text class label, one of `keyhole`, `LOF`, `balling`, `desirable`, `spatter formation` |
| `reasoning` | null | no native CoT in this dataset |
| `cate` | "C" | SFT category |
| `task` | "T-AM2" | unified task id |
| `metadata` | str (JSON) | split, provenance, units, `input`, license, and (for AM11/13) `taxonomy_note` |
## Notes
Leakage-guarded by normalized input fields: answer/outcome columns (`meltpool shape`, non-mode measurements, porosity, relative density, spatter, d/l·d/w·l/w) and provenance columns never enter `metadata.input` or the `Given inputs` block; mode labels appear only as task options. Raw MeltpoolNet process values are not exposed as naked numbers: velocity is normalized to mm/s, hatch/layer/beam dimensions to um, zero layer thickness is treated as unknown, and material composition/thermal properties are canonicalized from Akbari et al. Appendix A.9/A.10. This is a mode-only release based on HF revision `083cfafe758e72ecbfbaa049941668440300d516`: it keeps the source-native mode task and removes the former maintainer-defined quantile-label task because those labels were not physical or literature-backed gold. T-AM2 emits 1,236 unique `(query, annot)` rows from 1,249 labeled source rows after folding exact duplicates with `metadata.merged_paper_ids` / provenance preserved. Hatch/layer completeness is metadata, not a classification filter. T-AM2 remains 5-way and imbalanced (spatter formation has only 8 rows). VED is retained only as a reference metric in metadata. The causal metadata scaffold is `metadata.causal_features`: normalized enthalpy and laser intensity for mode. `metadata.causal_note` states that VED is a powder-bed density metric, not the single-track melt-pool mode driver. `metadata.cot_eligible` is true iff normalized enthalpy is computable from P,V,beam,rho,Cp,k,Tm (1,084 true / 152 false). Eligible rows also carry `metadata.cot_boundary_risk`, computed by same-material k=5 nearest neighbors in standardized (log normalized enthalpy, log intensity) space with majority-vote mode prediction and tied votes marked risky; counts are 387 true / 697 false / 152 null. No reasoning/CoT is generated here. Metadata is serialized as strict JSON with NaN/Infinity rejected. No split file is attached; if splitting is needed, use source provenance carefully and do not randomly split rows. **T-AM2** = AM task extension (`metadata.taxonomy_note`).
## Provenance & licensing
Underlying source: **MeltpoolNet — a meta-aggregation of ~hundreds of AM papers**. Upstream license: **no LICENSE (repo default = all-rights-reserved); meta-aggregation -> per-source clearance needed**.
Converted read-only into the unified schema; conversion + publish scripts live in
[`AI4Manufacturing/forge_model`](https://github.com/AI4Manufacturing/forge_model)
(`AM13_MeltpoolNet/` + `publish/push_am_to_hf.py`). Access is **gated (manual approval)**; clear the
upstream licence before any onward redistribution.