{"id":"W4404202047","doi":"10.1016/j.conctc.2024.101392","title":"A Bayesian adaptive feasibility design for rare diseases","year":2024,"lang":"en","type":"article","venue":"Contemporary Clinical Trials Communications","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Bayesian probability; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08256805,0.001588826,0.002236103,0.00168079,0.0009802907,0.001913841,0.002431263,0.003715273,0.01033895],"category_scores_gemma":[0.1385315,0.001596412,0.002034675,0.001034087,0.00342694,0.002711577,0.003299911,0.003610755,0.001296084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001808821,"about_ca_system_score_gemma":0.004586974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00117246,"about_ca_topic_score_gemma":0.0009861416,"domain_scores_codex":[0.9188488,0.07290033,0.001204281,0.00343573,0.002760291,0.0008505898],"domain_scores_gemma":[0.883562,0.09749177,0.006325827,0.006304441,0.004742007,0.001573997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0167652,0.001343545,0.009514398,0.001317498,0.0008529163,0.0006728264,0.001195211,0.2749238,0.005865777,0.4589173,0.004556348,0.224075],"study_design_scores_gemma":[0.006462435,0.008395107,0.003850191,0.0003703055,0.0004806682,0.0003939611,0.0001569991,0.7026967,0.002707964,0.2618544,0.01235902,0.00027233],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02062593,0.0002091482,0.9708524,0.0008196415,0.0001214812,0.004549008,0.0002131879,0.0003086327,0.002300692],"genre_scores_gemma":[0.3072737,0.0002620201,0.6715777,0.0006477574,0.000108309,0.01702312,0.0002814106,0.00006367131,0.002762337],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08256805,"threshold_uncertainty_score":0.4366668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7053743403086096,"score_gpt":0.5376744730215787,"score_spread":0.1676998672870309,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}