{"id":"W2763071712","doi":"10.1016/j.msard.2017.10.001","title":"The impact of treatment adherence on clinical and economic outcomes in multiple sclerosis: Real world evidence from Alberta, Canada","year":2017,"lang":"en","type":"article","venue":"Multiple Sclerosis and Related Disorders","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Novartis (Canada); Alberta Health Services; Université de Montréal; Hôpital Notre-Dame; University of Calgary","funders":"EMD Serono; Novartis Pharmaceuticals Canada; Multiple Sclerosis Society of Canada; Government of Alberta; Alberta Health Services; Genzyme; F. Hoffmann-La Roche; Teva Canada Innovation; Biogen Idec; Canadian Institutes of Health Research; Novartis","keywords":"Multiple sclerosis; Medicine; Real world evidence; Intensive care medicine; Psychiatry; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004999678,0.0004328636,0.0009831433,0.0001184283,0.0008266975,0.0001266294,0.000331343,0.0001717337,0.00004797783],"category_scores_gemma":[0.002548539,0.0002561578,0.0002953965,0.00008941758,0.001122295,0.000197217,0.0002416043,0.0004232291,0.000009413414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005214721,"about_ca_system_score_gemma":0.0005588281,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.972468,"about_ca_topic_score_gemma":0.9838419,"domain_scores_codex":[0.9971963,0.0002197646,0.0009533925,0.0007474371,0.0002932448,0.0005899172],"domain_scores_gemma":[0.9932629,0.004882756,0.000445483,0.0009978703,0.00006043337,0.0003505716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009306094,0.0002411104,0.9509107,0.00001262335,0.0006550727,0.00000190362,0.0003955483,0.0001961984,0.0004865619,0.000004965887,0.0003716834,0.04579305],"study_design_scores_gemma":[0.008729975,0.0009686293,0.9798724,0.0008903284,0.00007864353,3.315972e-7,0.0003804649,0.008618268,0.0001114788,0.00002255618,0.00007948958,0.0002474528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947312,0.001344257,3.083219e-7,0.001950722,0.0002653546,0.001059521,0.0001297896,0.00001723763,0.000501595],"genre_scores_gemma":[0.9325365,0.06679277,0.00004494734,0.00002114599,0.00003273736,0.0001113718,0.00001222219,0.00003355027,0.0004147487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06544852,"threshold_uncertainty_score":0.9999891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1257657545443929,"score_gpt":0.356829119700862,"score_spread":0.2310633651564691,"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."}}