{"id":"W2465429247","doi":"10.1212/wnl.0000000000002887","title":"Health insurance affects the use of disease-modifying therapy in multiple sclerosis","year":2016,"lang":"en","type":"article","venue":"Neurology","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Canadian Institutes of Health Research; EMD Serono; MedDay Pharmaceuticals; Multiple Sclerosis Society of Canada; Genentech; Multiple Sclerosis Society; Research Manitoba; National Institute of Neurological Disorders and Stroke; Teva Pharmaceutical Industries; University of Alabama at Birmingham; Cleveland Clinic; University of Alabama; Biogen; Sanofi; U.S. Department of Defense; Janssen Pharmaceuticals; Gilead Sciences; National Heart, Lung, and Blood Institute; Pfizer","keywords":"Denial; Odds; Actuarial science; Odds ratio; Health insurance; Group insurance; Medicine; Logistic regression; General insurance; Business; Insurance policy; Psychology; Income protection insurance; Health care; Internal medicine; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002712086,0.0001247227,0.0003586902,0.000119732,0.00008224418,0.000005347877,0.0001326287,0.0000460754,0.00001656271],"category_scores_gemma":[0.001309853,0.00006273752,0.00007492728,0.0002080775,0.0003453534,0.00007478514,0.00009195232,0.0001978388,0.000009362881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002712663,"about_ca_system_score_gemma":0.00008678185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004382057,"about_ca_topic_score_gemma":0.0004116338,"domain_scores_codex":[0.9983703,0.0004406744,0.0002272493,0.0002914104,0.0002549949,0.0004153927],"domain_scores_gemma":[0.9974533,0.001809772,0.00009716868,0.0004496595,0.00005951524,0.0001305804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002575286,0.000156849,0.8629469,0.00004399612,0.00002231855,0.00000764681,0.0001542385,0.0000214751,0.03172263,0.0000147009,0.0006871757,0.1016468],"study_design_scores_gemma":[0.003293415,0.001046805,0.9917678,0.0001012385,0.000001632985,0.000001903632,0.000002024442,0.0002282036,0.0006165631,0.00000962246,0.002881828,0.0000490081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574242,0.0005748211,0.00003870682,0.04105665,0.00009485077,0.0007402763,0.00002992837,0.0000293854,0.00001121501],"genre_scores_gemma":[0.9877757,0.008142476,0.00006769785,0.003827719,0.00005418012,0.00009318489,0.000001364187,0.00001967691,0.00001796991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1288208,"threshold_uncertainty_score":0.2558362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2158484439859246,"score_gpt":0.3422619353593869,"score_spread":0.1264134913734622,"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."}}