README.md

metadata

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