metadata
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
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