---
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