datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
reasoning-constraint-loss-attribution-v0.1
Reasoning Constraint Loss Attribution v0.1
A SIOS research dataset for identifying when a governing constraint ceases to regulate a reasoning trajectory, locating the first point of loss, attributing the lost constraint, and identifying the structural mechanism that produced the loss.
Repository:
ClarusC64/reasoning-constraint-loss-attribution-v0.1
Version:
0.1.0
Publisher:
Clarus Invariant
Framework:
SIOS
Dataset identity
Reasoning Constraint Loss Attribution… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/reasoning-constraint-loss-attribution-v0.1.clinical-constraint-pressure-v0.1
What this dataset does
This dataset tests whether a model can estimate how close a patient is to a treatment boundary.
The task is not to predict diagnosis.
The task is to classify pressure on the patient system.
Core stability idea
A patient may be stable at the present moment while operating close to a boundary.
Constraint pressure increases when support needs rise and reserve capacity falls.
The model must classify whether pressure is low, medium, or high.… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-constraint-pressure-v0.1.clinical-constraint-pressure-v0.2
What this dataset does
This dataset tests whether a model can estimate clinical constraint pressure.
The task is not to identify current illness severity.
The task is to classify how much pressure the patient system is under relative to available reserve.
What changed in v0.2
v0.2 adds counterfactual and adversarial cases.
Some rows have the same oxygen requirement or vasopressor requirement but different reserve states.
Some high-looking cases have preserved… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-constraint-pressure-v0.2.saelarien-constraint-experiment-03-recovery-collapse-mismatch
Saelariën Constraint Experiment 03: Recovery–Collapse Mismatch
Summary
This dataset extends Experiment 01, which established that collapse emerges when entropy injection exceeds a system’s capacity to maintain coherent state.
Experiment 03 isolates a different question: whether recovery dynamics uniquely characterize proximity to collapse.
The results show they do not.
Systems with indistinguishable recovery profiles can resolve into both stable and collapsed outcomes.… See the full description on the dataset page: https://huggingface.co/datasets/Saelarien/saelarien-constraint-experiment-03-recovery-collapse-mismatch.clinical-decision-constraint-integrity-v0.2
Clinical Decision Constraint Integrity v0.2
What this is
A small dataset that tests one question:
Can you detect when a clinical decision system is moving toward constraint failure, not just carrying decision pressure?
This repo focuses on decision constraint integrity.
It models a system where:
constraint clarity may weaken
option space may narrow or distort
conflict pressure may rise
decision friction may destabilize clean action before overt failure appears… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-decision-constraint-integrity-v0.2.clinical-constraint-absorbability-ordering-v0.3
Clinical Constraint Absorbability Ordering v0.3
This dataset tests whether a model can infer the first absorbable repair move under hidden clinical constraint competition.
The task is not diagnosis.
The task is not ordinary treatment selection.
The task is recovery-control sequencing:
What can this system safely absorb first?
Core idea
A patient may show multiple abnormal signals at once.
Examples:
elevated TSH
low ferritin
sleep disruption
high stress load
high repair… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-constraint-absorbability-ordering-v0.3.oncology-precancer-constraint-geometry-v0.2
What this dataset does
This dataset tests whether a model can detect pre-cancer instability from constraint geometry rather than single-variable thresholds.
The task is not cancer diagnosis.
The task is to classify whether a synthetic tissue ecology has crossed into a persistent instability transition.
Core Stability Idea
The dataset represents a stability-transition hypothesis.
Cancer vulnerability may begin when tissue regulation loses self-correcting coherence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-precancer-constraint-geometry-v0.2.