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dataset card: add evals config

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  1. README.md +13 -0
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@@ -21,6 +21,8 @@ configs:
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  data_files: data/train_ornith.jsonl
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  - config_name: train_blended
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  data_files: data/train_blended.jsonl
 
 
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  ---
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  # Plumb
@@ -42,6 +44,17 @@ Leakprobe vs benchmark: exact signature overlap 0.
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  | Ornith-only | 58 | 0.241 [0.214, 0.268] | 0.111 [0.098, 0.124] | 0.084 |
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  | blend | 281 | 0.334 [0.306, 0.363] | 0.374 [0.342, 0.406] | 0.228 |
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  CIs: 10k bootstrap, seed 11. Adapters: [`handseeded`](https://huggingface.co/caiotheodoro/plumb-handseeded) · [`ornith`](https://huggingface.co/caiotheodoro/plumb-ornith) · [`blended`](https://huggingface.co/caiotheodoro/plumb-blended). N=18 mix/error and pow-* / leaked-anchor grows are not here.
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  ```python
 
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  data_files: data/train_ornith.jsonl
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  - config_name: train_blended
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  data_files: data/train_blended.jsonl
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+ - config_name: evals
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+ data_files: data/evals/evals.jsonl
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  ---
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  # Plumb
 
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  | Ornith-only | 58 | 0.241 [0.214, 0.268] | 0.111 [0.098, 0.124] | 0.084 |
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  | blend | 281 | 0.334 [0.306, 0.363] | 0.374 [0.342, 0.406] | 0.228 |
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+ The `evals` config has all 15 published rows (full size, equal-N@58 random and stratified, clean equal-N@18) with their CIs, so the tables in the post are reproducible without rerunning anything:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ evals = load_dataset("caiotheodoro/plumb", "evals", split="train")
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+ [r for r in evals if r["group"] == "full_size"]
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+ ```
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+
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+ Raw per-prediction dumps live at `data/evals/eval-{handseeded,ornith,blended}.json` and `PATH_A_RESULTS.json`. Those are artifacts, not configs; fetch them with `hf_hub_download`.
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+
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  CIs: 10k bootstrap, seed 11. Adapters: [`handseeded`](https://huggingface.co/caiotheodoro/plumb-handseeded) · [`ornith`](https://huggingface.co/caiotheodoro/plumb-ornith) · [`blended`](https://huggingface.co/caiotheodoro/plumb-blended). N=18 mix/error and pow-* / leaked-anchor grows are not here.
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  ```python