scenario_id string | scenario_text string | claim string | label int64 |
|---|---|---|---|
train_001 | The platform automatically shifts compute resources as demand increases. | The system shows adaptive load management. | 1 |
train_002 | The platform uses the same resource allocation regardless of demand level. | The system shows adaptive load management. | 0 |
train_003 | A clinic expands triage capacity during peak patient arrivals. | The clinic shows adaptive load management. | 1 |
train_004 | A clinic keeps staffing fixed despite large swings in patient volume. | The clinic shows adaptive load management. | 0 |
train_005 | A warehouse activates reserve staff during seasonal demand spikes. | The warehouse shows adaptive load management. | 1 |
train_006 | A warehouse operates with identical staffing regardless of order volume. | The warehouse shows adaptive load management. | 0 |
train_007 | A database adds replicas as transaction volume increases. | The database shows adaptive load management. | 1 |
train_008 | A database keeps fixed capacity while transaction demand doubles. | The database shows adaptive load management. | 0 |
train_009 | A support team dynamically reassigns staff to overloaded queues. | The support system shows adaptive load management. | 1 |
train_010 | A support team maintains fixed assignment despite growing queue imbalance. | The support system shows adaptive load management. | 0 |
train_011 | A logistics network reroutes deliveries around congested regions. | The logistics system shows adaptive load management. | 1 |
train_012 | A logistics network continues using overloaded routes despite available alternatives. | The logistics system shows adaptive load management. | 0 |
train_013 | A machine reduces operating speed during thermal stress and restores speed after cooling. | The machine shows adaptive load management. | 1 |
train_014 | A machine maintains maximum speed regardless of thermal condition. | The machine shows adaptive load management. | 0 |
train_015 | A project team adjusts priorities as workload changes. | The project shows adaptive load management. | 1 |
train_016 | A project team keeps the same priorities despite major workload shifts. | The project shows adaptive load management. | 0 |
train_017 | A hospital ward redistributes patients when occupancy rises. | The ward shows adaptive load management. | 1 |
train_018 | A hospital ward keeps fixed allocation despite occupancy imbalance. | The ward shows adaptive load management. | 0 |
train_019 | A payment processor throttles noncritical jobs during transaction surges. | The platform shows adaptive load management. | 1 |
train_020 | A payment processor treats all workloads identically during transaction surges. | The platform shows adaptive load management. | 0 |
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
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