Datasets:
File size: 1,497 Bytes
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language:
- en
license: mit
pretty_name: Clinical Etiological Basin Identification v0.1
dataset_name: clinical-etiological-basin-identification-v0.1
tags:
- clarusc64
- clinical
- long-covid
- me-cfs
- autoimmune
- basin-map
- topology
task_categories:
- text-classification
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/train.csv
- split: test
path: data/test.csv
---
What this dataset tests
Whether a model can identify the stable illness basin
from multi-system features, independent of trigger.
Required outputs
- basin_id
- basin_stability_score_0_100
- defining_state_features_top5
Basin labels
- basin_A_inflammatory_autonomic
- basin_B_mito_metabolic_fatigue
- basin_C_neuroimmune_cognitive
- basin_D_mast_cell_histamine_like
- basin_E_autoimmune_multisystem
Typical failures
- using precipitating event as the primary classifier
- listing symptoms without identifying the basin state
- failing to name the top defining features
Suggested prompt wrapper
System
You assign an illness basin from multi-system features.
User
Immune
{immune_features}
Metabolic
{metabolic_features}
Autonomic
{autonomic_features}
Neurocognitive
{neurocognitive_features}
Dynamics
{symptom_dynamics}
Return
- basin id
- stability score
- top 5 defining features
- one sentence evidence
Citation
ClarusC64 dataset family
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