| --- |
| language: en |
| license: mit |
| task_categories: |
| - text-classification |
| tags: |
| - adaptive-load |
| - stability-geometry |
| - reasoning |
| - clarus |
| - sios |
| size_categories: |
| - n<1K |
| pretty_name: Adaptive Load Classification v0.1 |
| --- |
| |
| # What this dataset does |
|
|
| This dataset tests whether a model can detect adaptive load management. |
|
|
| The task is simple: |
|
|
| Given a scenario and an adaptive-load claim, predict whether the claim is supported. |
|
|
| # Core stability idea |
|
|
| Stable systems adapt load to available capacity. |
|
|
| Adaptive load management means the system changes allocation, routing, prioritization, scaling, staffing, or resource distribution as demand changes. |
|
|
| Non-adaptive systems keep fixed allocation despite changing conditions. |
|
|
| # Prediction target |
|
|
| Binary label: |
|
|
| - 1 = adaptive load management is present |
| - 0 = adaptive load management is not present |
|
|
| # 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 recognize dynamic resource allocation under changing demand conditions. |
| |
| License |
| |
| MIT |
