---
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