intervention-competition
control-intervention-competition-v0.1
What this dataset does
This dataset tests whether a model can identify the best stabilizing intervention among competing options.
The task is simple:
Given a scenario and a claim about the best intervention, predict whether the claim is correct.
Core stability idea
Systems often fail because the chosen action targets the visible symptom rather than the stability constraint.
This dataset targets that failure mode.
A good intervention reduces pressure, restores buffer… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/control-intervention-competition-v0.1.long-covid-intervention-competition-geometry-v0.1
What this dataset does
This dataset tests whether a model can identify the highest-leverage intervention pathway for a Long Covid biological state.
The task is intervention selection.
It is not diagnosis.
It is not clinical advice.
Core stability idea
Patients with similar symptoms may require different intervention sequences.
The model must identify the dominant constraint within the system.
The central challenge is to distinguish symptom burden from intervention… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/long-covid-intervention-competition-geometry-v0.1.clinical-intervention-competition-sepsis-v1Clinical Intervention Competition Sepsis Detection
Overview
This dataset tests whether a model can determine which intervention pathway best stabilizes a sepsis-like clinical system.
In real clinical settings multiple interventions may be available at the same time. Each intervention affects system dynamics differently. Some actions move the system toward recovery while others fail to meaningfully counteract the instability trajectory.
The task is to determine which intervention most… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-intervention-competition-sepsis-v1.