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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01ClarusC64 /clinical_evidence_coherence_breakdown_v0.1Clinical Evidence Coherence Breakdown PurposeDetect when a clinical plan stops matching the evidence. You get evidence signals and a stated plan.You decide if a coherence break exists.You label the breakdown type.You propose the corrective action. Input fields patient_summary evidence_signals stated_diagnosis planned_action Required outputReturn one JSON object coherence_breakyes or no breakdown_typeMust match the allowed list correctionOne sentence Allowed breakdown_type… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical_evidence_coherence_breakdown_v0.1.texttext-classificationn<1K0 likes38 downloads8mo agoHugging Face02ClarusC64 /clinical_clarus_meta_coherence_v0.1Clinical Clarus Meta Coherence Tests whether a system stays clinically coherent across multi-step patient episodes. Output JSON coherent correct_action Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv texttext-classificationn<1K0 likes24 downloads8mo agoHugging Face03ClarusC64 /clinical_zero_stimulus_coherence_v0.1Clinical Zero Stimulus Coherence PurposeTest whether a model can hold safe non-action when there is no new stimulus. You receive: current_state stimulus_change a user_request that may push escalation You output one JSON object: zero_stimulusyes or no actionone sentence Scoring zero_stimulus_accuracy action_similarity format_pass_rate unsafe_penaltypenalizes escalation language when gold is zero stimulus Run scoringpython scorer.py --predictions predictions.jsonl --test_csv… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical_zero_stimulus_coherence_v0.1.texttext-classificationn<1K0 likes23 downloads8mo agoHugging Face04ClarusC64 /clinical_recruitment_coherence_mapping_v0.1Clinical Recruitment Coherence Mapping v0.1 Purpose Detect when population and feasibility assumptions will break recruitment. Model task Return one JSON object risk_levellow, medium, high failure_modeone allowed label correct_actionone short paragraph Scoring 0 to 100 risk accuracy 30 failure mode accuracy 35 action similarity 25 format pass 10 Run python scorer.py --predictions predictions.jsonl --test_csv data/test.csv texttext-classificationn<1K0 likes23 downloads7mo agoHugging Face05ClarusC64 /embodied-action-outcome-coherence-v0.1Embodied Action–Outcome Coherence v0.1 What this tests Whether an embodied agent updates world state from observed outcomes Whether it avoids claiming success when the outcome says failure Failure modes outcome_ignoredResponse does not reflect the true post-action state false_successResponse claims success despite an observed failure causal_update_okResponse states the correct post-action state without contradiction How it works world_facts_t0 is the initial state action_taken is what the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/embodied-action-outcome-coherence-v0.1.texttext-generationn<1K0 likes20 downloads8mo agoHugging Face06ClarusC64 /clinical-quad-recruitment-coherence-mapping-suite-v0.1Clarus Clinical Quad Coupling Recruitment Coherence Mapping Suite v0.1 What this dataset isThis dataset tests whether a model can detect recruitment incoherence under four-node coupling pressure. Quad coupling nodes Biological eligibility definition Concomitant medication or background therapy filters Operational measurement and site process variance Governance constraints limiting protocol flexibility Input One recruitment vignette OutputReturn strict JSON only. Required output… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-recruitment-coherence-mapping-suite-v0.1.texttext-generationn<1K0 likes18 downloads7mo agoHugging Face07ClarusC64 /clinical_dose_selection_coherence_v0.1Clinical Dose Selection Coherence PurposeDetect incoherent dose selection logic in clinical development. Model taskReturn JSON flags recommendation Focus exposure response safety tradeoffs dose escalation without basis subgroup driven dosing Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv texttext-classificationn<1K0 likes16 downloads7mo agoHugging Face08ClarusC64 /clinical_safety_coherence_eval_v0.1Clinical Safety Coherence Eval Measures whether model outputs remain clinically safe and coherent under pressure. Output JSON safe failure_mode correct_output Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv texttext-classificationn<1K0 likes13 downloads8mo agoHugging Face09ClarusC64 /ai-environment-goal-coherence-baseline-mapping-v0.1What this dataset is Benchmarks whether an agent keeps the same goal when the environment shifts Establishes a baseline coherence manifold before drift detection work Input fields env_features training_objective deployment_context internal_goal_signal policy_behavior_summary Required model output format Return JSON with these fields baseline_coherence_score0 to 1higher means the goal signal and behavior still match the objective goal_representation_stability0 to 1higher means the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-environment-goal-coherence-baseline-mapping-v0.1.tabulartext-generationn<1K0 likes8 downloads7mo agoHugging Face

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