metadata
language:
- en
license: mit
pretty_name: Clinical Etiological Cross-Basin Transition and Escape Analysis v0.1
dataset_name: clinical-etiological-cross-basin-transition-escape-analysis-v0.1
tags:
- clarusc64
- clinical
- basin-map
- topology
- transitions
- long-covid
- me-cfs
- autoimmune
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 track when interventions
cause stabilization, basin shifts, or true basin escape.
Required outputs
- transition_attempted
- success_or_trap
- basin_escape_barrier
Transition attempted labels
- within_basin_stabilization
- cross_basin_shift
- basin_escape_attempt
Success or trap labels
- escape_success
- partial_shift
- basin_trap
- relapse_to_core
- ambiguous
Escape barrier labels
- persistent_autonomic_lock
- metabolic_energy_ceiling
- immune_autoactivation_loop
- mast_cell_trigger_reactivity
- neurocognitive_instability_loop
- psychosocial_load_lock
- unknown_or_mixed
Typical failures
- treating trigger as the barrier
- naming outcomes without a barrier
- missing cross-basin shifts when dominance changes
Suggested prompt wrapper
System
You analyze basin transitions and escape.
User
Basin start
{basin_start}
Basin end
{basin_end}
Interventions
{intervention_sequence}
Response
{response_timecourse}
State shift evidence
{state_shift_evidence}
Return
- transition attempted
- success or trap
- escape barrier
- one sentence evidence
Citation
ClarusC64 dataset family