| --- |
| language: en |
| license: mit |
| task_categories: |
| - text-classification |
| tags: |
| - decision-timing |
| - control-geometry |
| - reasoning |
| - clarus |
| - sios |
| size_categories: |
| - n<1K |
| pretty_name: Decision Timing Classification v0.1 |
| --- |
| |
| # What this dataset does |
|
|
| This dataset tests whether a model can judge whether action is being taken at the right time. |
|
|
| # Core stability idea |
|
|
| Good decisions depend on timing. |
|
|
| The same action can be stabilizing early and useless late. |
|
|
| Decision timing is appropriate when action occurs before buffers close, damage spreads, or recovery options disappear. |
|
|
| # Prediction target |
|
|
| Binary label: |
|
|
| - 1 = decision timing is appropriate |
| - 0 = decision timing is too late or poorly timed |
|
|
| # Row structure |
|
|
| Each row contains: |
|
|
| - scenario_id |
| - scenario_text |
| - claim |
| - label |
|
|
| # Files |
|
|
| - data/train.csv |
| - data/test.csv |
| - scorer.py |
| - README.md |
|
|
| # Evaluation |
|
|
| ```bash |
| python scorer.py --predictions predictions.csv --truth data/test.csv |
| |
| Structural Note |
| |
| This dataset is intentionally small. |
| |
| Its purpose is to test whether a model can detect timing-sensitive control windows. |
| |
| License |
| |
| MIT |
