{"id":"W1988510033","doi":"10.1177/1352458514556303","title":"Development and validation of an administrative data algorithm to estimate the disease burden and epidemiology of multiple sclerosis in Ontario, Canada","year":2014,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; St. Michael's Hospital; The Scarborough Hospital; Health Sciences Centre; Women's College Hospital; University Health Network; University of Toronto; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Epidemiology; Medicine; Multiple sclerosis; Incidence (geometry); Algorithm; Disease burden; Population; Demography; Computer science; Internal medicine; Environmental health; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01021324,0.00067295,0.0007365843,0.003168376,0.001709628,0.002220236,0.001818128,0.00053814,0.001224898],"category_scores_gemma":[0.04401249,0.000458133,0.0008261407,0.003485062,0.0004967324,0.0006226244,0.001004988,0.000609044,0.0003924499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02543453,"about_ca_system_score_gemma":0.0514314,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9655398,"about_ca_topic_score_gemma":0.9565098,"domain_scores_codex":[0.9947723,0.001233863,0.0007633044,0.0005666886,0.002309901,0.000353876],"domain_scores_gemma":[0.9690714,0.004977384,0.002019663,0.0009289568,0.02249942,0.0005031007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004512216,0.0002170681,0.8316037,0.0003729232,0.000352808,0.0001383048,0.0005924209,0.02752543,0.0008991577,0.001146685,0.01340629,0.1232939],"study_design_scores_gemma":[0.0003592489,0.0001331297,0.6893216,0.0003225522,0.0003238674,0.0001742632,0.000583988,0.2950973,0.001901366,0.0006751341,0.0110277,0.00007980392],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8145834,0.00242251,0.1202967,0.003108701,0.0002121601,0.005945682,0.03416099,0.002049573,0.01722031],"genre_scores_gemma":[0.8105663,0.0007604865,0.1728898,0.0003083825,0.00003202659,0.001060741,0.01256115,0.0001089071,0.001712197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03446019,"threshold_uncertainty_score":0.1845413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2355473658533757,"score_gpt":0.372692536325335,"score_spread":0.1371451704719593,"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."}}