{"id":"W3127636206","doi":"10.26443/mjm.v7i1.634","title":"The Epidemiology Study in Multiple Sclerosis - Relevance to Natural History","year":2020,"lang":"en","type":"article","venue":"McGill Journal of Medicine","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. John’s Health Sciences Centre","funders":"","keywords":"Natural history; Epidemiology; Multiple sclerosis; Medicine; Relevance (law); Context (archaeology); Categorization; Disease; Cluster (spacecraft); Natural (archaeology); Etiology; Data science; Pathology; Immunology; Artificial intelligence; Computer science; Geography; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02114281,0.0001753773,0.001064851,0.003795721,0.0005906046,0.001989935,0.0004856981,0.0009552062,0.002145943],"category_scores_gemma":[0.07475232,0.0002051628,0.001046891,0.008681175,0.001045442,0.001725199,0.001243359,0.0009988957,0.0001531697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001160395,"about_ca_system_score_gemma":0.002459976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004616188,"about_ca_topic_score_gemma":0.00774233,"domain_scores_codex":[0.9708349,0.02325549,0.002729762,0.001110945,0.001793457,0.0002753915],"domain_scores_gemma":[0.9145663,0.07118286,0.00814678,0.002039755,0.002630552,0.001433727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001106301,0.00006829408,0.7019277,0.03309318,0.007644115,0.00103699,0.004519317,0.0002780704,0.000463035,0.02947872,0.009492136,0.2108922],"study_design_scores_gemma":[0.0001970419,0.0005385528,0.9021761,0.02720074,0.004540984,0.001910034,0.002732296,0.0004140075,0.0002228945,0.0100822,0.04992473,0.00006044545],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0812749,0.881625,0.002560496,0.02462522,0.001622411,0.0003151153,0.001789315,0.00001408082,0.006173577],"genre_scores_gemma":[0.6784513,0.304496,0.004913609,0.006642339,0.002374478,0.0008345732,0.0009196447,0.00002246449,0.001345543],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02114281,"threshold_uncertainty_score":0.1118152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.30502307196755,"score_gpt":0.380468718348339,"score_spread":0.07544564638078899,"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."}}