{"id":"W4382883108","doi":"10.1016/j.msard.2023.104869","title":"Assessing the utility of magnetic resonance imaging-based “SuStaIn” disease subtyping for precision medicine in relapsing-remitting and secondary progressive multiple sclerosis","year":2023,"lang":"en","type":"article","venue":"Multiple Sclerosis and Related Disorders","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; NeuroRx Research (Canada)","funders":"International Progressive MS Alliance; Biogen","keywords":"Subtyping; Natalizumab; Medicine; Multiple sclerosis; Magnetic resonance imaging; Oncology; Clinical trial; Disease; Internal medicine; Placebo; Progressive disease; Pathology; Immunology; Radiology","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":[0.03561547,0.000815284,0.001125585,0.001992453,0.0007741661,0.001864836,0.001029213,0.001361906,0.0007960511],"category_scores_gemma":[0.07274347,0.000397457,0.001390459,0.001350519,0.001312639,0.002473724,0.001639488,0.0007237663,0.0001814776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000611225,"about_ca_system_score_gemma":0.00126492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003325173,"about_ca_topic_score_gemma":0.005920168,"domain_scores_codex":[0.9848413,0.01068665,0.001444339,0.0008355162,0.001825559,0.0003665639],"domain_scores_gemma":[0.9409934,0.03837394,0.008704616,0.005739333,0.005382023,0.0008067216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02303175,0.00063467,0.9016075,0.0007637126,0.006104192,0.0001641439,0.001342636,0.001583869,0.002602686,0.0008838275,0.0005883581,0.06069273],"study_design_scores_gemma":[0.0013603,0.01825016,0.9572176,0.0003872871,0.006465434,0.000536162,0.001142737,0.005991959,0.003650049,0.002219022,0.002686397,0.00009304836],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900788,0.005536672,0.00185231,0.0003474437,0.00007280733,0.0001451052,0.0002808474,0.00001508396,0.001670917],"genre_scores_gemma":[0.9981713,0.0002671257,0.001190036,0.00008274656,0.00003648052,0.00003060937,0.0001222551,0.000003174841,0.00009628979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03561547,"threshold_uncertainty_score":0.1883549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04748384130623075,"score_gpt":0.3108504081322997,"score_spread":0.263366566826069,"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."}}