{"id":"W4401775550","doi":"10.1002/hbm.26816","title":"Pooled analysis of multiple sclerosis findings on multisite 7 Tesla <scp>MRI</scp>: Protocol and initial observations","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University; NeuroRx Research (Canada); Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health; Race to Erase MS; Canadian Institutes of Health Research; Conrad N. Hilton Foundation; Novartis; Bristol-Myers Squibb; Roche; EMD Serono; National Multiple Sclerosis Society","keywords":"Multiple sclerosis; Multicenter study; Pooling; Medicine; Magnetic resonance imaging; Protocol (science); Medical physics; Nuclear medicine; Computer science; Radiology; Artificial intelligence; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.09680796,0.001896022,0.002299034,0.002852986,0.001972696,0.00226047,0.002592846,0.001484689,0.005825259],"category_scores_gemma":[0.10704,0.00202628,0.003035062,0.004409084,0.002166632,0.001429389,0.00369402,0.002081744,0.004002323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002055414,"about_ca_system_score_gemma":0.007692214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001905144,"about_ca_topic_score_gemma":0.002717842,"domain_scores_codex":[0.9603247,0.02314317,0.007696768,0.002980899,0.005106894,0.0007474616],"domain_scores_gemma":[0.94372,0.01112157,0.006016156,0.01564995,0.02216512,0.001327231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.1627563,0.01268119,0.08796111,0.02878387,0.009828907,0.002871563,0.01075709,0.02081002,0.0542288,0.01611811,0.1005045,0.4926985],"study_design_scores_gemma":[0.0423776,0.057081,0.4143616,0.01273599,0.01047293,0.003009569,0.003340805,0.01857652,0.05971929,0.02131086,0.3553515,0.001662429],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.06425904,0.002222656,0.1824025,0.001086297,0.0006560448,0.7162347,0.02329997,0.001341099,0.008497717],"genre_scores_gemma":[0.04852491,0.0008390975,0.1078151,0.0004662718,0.0001792572,0.8314165,0.009483553,0.0003248492,0.0009503911],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.09680796,"threshold_uncertainty_score":0.5119755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1631429870221415,"score_gpt":0.3695137627793779,"score_spread":0.2063707757572364,"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."}}