datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
clinical_alignment_recovery_dynamics_v0.1Clinical Alignment Recovery Dynamics
Measures whether a model corrects earlier clinical errors when new signals appear.
Output JSON
recovered
recovery_type
correct_action
Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv
alignment_recovery_dynamics_v01Clarus Alignment Recovery Dynamics v0.1
This dataset measures recovery after an alignment flip.
Focus
Not only whether a system flips
But whether it can recover
And whether it relapses under renewed pressure
Design
One row per step
Steps form a trajectory grouped by case_id
A recovery window defines how quickly recovery must occur
Columns
flip_signal_expected
none, early_warning, flip, cascade
first_flip_step_expected
First step where a flip is expected, or -1
recovery_expected
true if… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/alignment_recovery_dynamics_v01.