{"id":"W2153466844","doi":"10.1136/bmjopen-2013-004073","title":"UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model","year":2014,"lang":"en","type":"article","venue":"BMJ Open","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada","keywords":"Medicine; Cohort; Natural history; Covariate; Cohort study; Demography; Gerontology; Physical therapy; Internal medicine; Statistics","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":[0.007434648,0.0004060088,0.0009313085,0.001186955,0.0006461091,0.001210181,0.002488708,0.001712753,0.005634199],"category_scores_gemma":[0.02372195,0.0005265724,0.001152559,0.001782511,0.0006917439,0.0008759153,0.001155311,0.001525564,0.0009956496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003031425,"about_ca_system_score_gemma":0.002137269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1263636,"about_ca_topic_score_gemma":0.09798608,"domain_scores_codex":[0.9977665,0.001276077,0.0001485758,0.0004173177,0.0002186529,0.0001729083],"domain_scores_gemma":[0.9870679,0.007095155,0.001267519,0.002813113,0.001351256,0.0004050475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006498487,0.001082148,0.2376714,0.0007573189,0.0007173543,0.001991724,0.0009019598,0.5189387,0.0007223793,0.03531213,0.1249273,0.07047912],"study_design_scores_gemma":[0.001249891,0.0002749779,0.05963442,0.0001658529,0.000182928,0.000606651,0.0001627544,0.8977721,0.0003431751,0.01495829,0.02452498,0.0001239515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6596909,0.001287077,0.07850481,0.004351699,0.0001994692,0.001862267,0.2465691,0.001458063,0.006076585],"genre_scores_gemma":[0.7465155,0.0003933666,0.05431307,0.0004057942,0.00009250139,0.001577449,0.1925479,0.00009581489,0.004058602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1263636,"threshold_uncertainty_score":0.2512561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1971776280240683,"score_gpt":0.4022604708018573,"score_spread":0.205082842777789,"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."}}