Update README.md

README.md

@@ -106,8 +106,9 @@ merged = scalar.merge(per_output, on="evaluation_id", suffixes=("_scalar", "_qua
 Five CSV files, joinable as described above. `domain` and `stage` can be recovered for any record from `prompts_workflow.csv` or `model_outputs.csv`.
 ### `prompts_workflow.csv` — 95 rows (one per prompt)
 
-| `prompt_id` | Readable prompt identifier (e.g. `ad_image_idea_4152`). |
-| `raw_prompt_id` | Original source numeric id for the prompt. |
+| Column | Description |
+|---|---|
+| `prompt_id` | Readable prompt identifier. |
 | `domain` | One of the five creative domains. |
 | `stage` | `Ideation`, `Mockup`, or `Refinement`. |
 | `prompt_text` | The text prompt presented to the models. |
@@ -116,6 +117,8 @@ Five CSV files, joinable as described above. `domain` and `stage` can be recover
 
 ### `model_outputs.csv` — 380 rows (one per prompt × model)
 
+| Column | Description |
+|---|---|
 | `content_id` | Per-asset primary key (UUID). |
 | `prompt_id` | Foreign key to `prompts_workflow.csv`. |
 | `domain`, `stage` | Creative domain and workflow phase. |
@@ -138,6 +141,7 @@ Forced-choice head-to-head preferences. For each prompt, evaluators compared all
 | `content_id_left`, `content_id_right`, `content_id_chosen` | The specific `model_outputs.content_id` assets shown and selected. |
 
 **Sampling note.** Each domain has four candidate models (six possible pairs). Left/right position bias is negligible (49.8% left / 50.2% right).
+
 ### `scalar_feedback.csv` — 812 rows
 
 1-5 Likert ratings on three dimensions, ordered from most objective to most taste-driven. **Note:** scalar ratings were collected only for the two code domains (Desktop App, Landing Pages) in this release; image and video domains are not rated here.
@@ -192,7 +196,7 @@ To commission an evaluation or dataset for your domain, reach out through [contr
 
 ## Provenance and consent
 
-Evaluations were collected with consent from professional creatives sourced from Contra's top-earning talent, selected by skillset and matched to the model category most relevant to their workflow. Evaluators are represented by anonymized numeric `user_id` values and a `user_core_skill` label only; no names or direct identifiers are included. Qualitative feedback was additionally stripped of personally identifiable information and model identities before processing. Model identities were blinded and output order randomized during evaluation to prevent brand bias.
+Evaluations were collected with consent from professional creatives sourced from Contra's top-earning talent, selected by skillset and matched to the model category most relevant to their workflow. Evaluators are represented by anonymized numeric `evaluator_id` values and a `user_core_skill` label only; no names or direct identifiers are included. Qualitative feedback was additionally stripped of personally identifiable information and model identities before processing. Model identities were blinded and output order randomized during evaluation to prevent brand bias.
 
 ## Citation