{"id":"W2984612893","doi":"10.1177/2055217319885983","title":"Machine learning in secondary progressive multiple sclerosis: an improved predictive model for short-term disability progression","year":2019,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal - Experimental Translational and Clinical","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Ottawa Hospital; University of British Columbia","funders":"Multiple Sclerosis Society of Canada","keywords":"Expanded Disability Status Scale; Logistic regression; Multiple sclerosis; Machine learning; Medicine; Receiver operating characteristic; Support vector machine; Clinical trial; Physical therapy; Artificial intelligence; Internal medicine; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001628381,0.0005061419,0.001000594,0.0001499999,0.0005563876,0.0001534076,0.0002453388,0.0003403254,0.000165265],"category_scores_gemma":[0.0005073346,0.0004048212,0.0005449382,0.0001832168,0.0006963296,0.0008451227,0.0001454878,0.001574301,0.000004542138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002170723,"about_ca_system_score_gemma":0.0002334337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002293608,"about_ca_topic_score_gemma":0.00007542526,"domain_scores_codex":[0.9953225,0.0004233438,0.001581378,0.001051343,0.0008635245,0.0007578926],"domain_scores_gemma":[0.9972682,0.001105422,0.000286631,0.0003072381,0.0002991592,0.0007333768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009266494,0.003986627,0.8123025,0.0001199289,0.0002480439,0.00000417507,0.001387621,0.0004873687,0.08768028,0.000009388551,0.00001007154,0.08449752],"study_design_scores_gemma":[0.01231169,0.002275198,0.5345078,0.0005094256,0.00004700656,0.0000170259,0.0006265501,0.4471372,0.002249748,0.0000322131,0.000022002,0.0002640737],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907669,0.002911868,0.001476108,0.0008190186,0.0002361402,0.003368854,0.0002769124,0.00009289799,0.00005134382],"genre_scores_gemma":[0.9880466,0.0007897356,0.009767495,0.0001099785,0.0003954525,0.0004753518,0.0002895364,0.00007824517,0.00004754591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4466499,"threshold_uncertainty_score":0.9998404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1566684101755616,"score_gpt":0.4037198011592445,"score_spread":0.2470513909836829,"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."}}