ClarusC64/clinical-personal-deviation-vector-detection-v0.1
What this dataset tests Whether a model can detect deviation from a person's own coherent basinusing baseline envelope and coupling structure. Required outputs deviation_vector deviation_severity_score_0_100 first_system_departing Deviation vector fields direction magnitude velocity coupling_loss onset_time cross_modal_consensus First system labels sleep_circadian autonomic immune_inflammatory metabolic neurocognitive gut_microbiome behavior_load… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-personal-deviation-vector-detection-v0.1.
What this dataset tests
Whether a model can detect deviation from a person's own coherent basin using baseline envelope and coupling structure.
Required outputs
- deviation_vector
- deviationseverityscore0100
- firstsystemdeparting
Deviation vector fields
- direction
- magnitude
- velocity
- coupling_loss
- onset_time
- crossmodalconsensus
First system labels
- sleep_circadian
- autonomic
- immune_inflammatory
- metabolic
- neurocognitive
- gut_microbiome
- behavior_load
- subjective_experience
Typical failures
- treating population thresholds as baseline
- outputting severity with no vector structure
- ignoring coupling changes
Suggested prompt wrapper
System
You detect deviation from a personal baseline.
User
Baseline signature {baseline_signature}
Baseline envelope {baseline_envelope}
Recent data Sleep: {recentdatasleep} Wearables: {recentdatawearables} Labs: {recentdatalabs} Behavior: {recentdatabehavior} Subjective: {recentdatasubjective}
Coupling changes {coupling_changes}
Return
- deviation vector with required fields
- severity score
- first system departing
- one sentence evidence
Citation
ClarusC64 dataset family