{"id":"W3091986019","doi":"10.1038/s41393-020-00563-8","title":"Building models for prediction: are we good at it?","year":2020,"lang":"en","type":"editorial","venue":"Spinal Cord","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"Université de Montréal","keywords":"Medicine; Physical medicine and rehabilitation","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":[0.0003808528,0.0004297375,0.0005630853,0.0001358746,0.0004280488,0.0002267832,0.001930009,0.0006784712,0.00001262408],"category_scores_gemma":[0.0006105204,0.0004489805,0.000243097,0.0003422075,0.00003509531,0.0003231416,0.0009501022,0.001446177,0.00003232025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004516885,"about_ca_system_score_gemma":0.0005287256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006412996,"about_ca_topic_score_gemma":0.00004049352,"domain_scores_codex":[0.9964091,0.0001279344,0.0005320846,0.001234956,0.001126158,0.0005697289],"domain_scores_gemma":[0.9974891,0.0003904145,0.0005300887,0.0008549026,0.0004456936,0.000289804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002926745,0.00001051144,0.00002356706,0.0009798803,0.00002491321,0.00002566959,0.00005578415,0.0007325069,0.000002548532,0.004933538,0.9823199,0.01059853],"study_design_scores_gemma":[0.0003111751,0.002119751,0.00001457515,0.0006314846,0.0000237303,0.000007484423,0.000006113195,0.1280226,0.000004882201,0.004823332,0.8637074,0.0003275631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00000402537,0.0007425634,0.41,0.01066335,0.5771248,0.0004532818,0.0002794495,0.0004028566,0.0003296491],"genre_scores_gemma":[0.0007479269,0.0001803294,0.07750759,0.0003845865,0.9188925,0.0002305668,0.0001546933,0.00008637988,0.001815409],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.3417677,"threshold_uncertainty_score":0.9997962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0758664853304112,"score_gpt":0.3717893381087868,"score_spread":0.2959228527783756,"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."}}