{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0226005,0.004308352,0.007116579,0.005642591,0.003259241,0.01210407,0.006317932,0.02734345,0.01089464],"category_scores_gemma":[0.09753089,0.002071354,0.003416375,0.003025957,0.006312333,0.009648368,0.002315253,0.03658727,0.01317811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004133905,"about_ca_system_score_gemma":0.006577721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005033417,"about_ca_topic_score_gemma":0.01236652,"domain_scores_codex":[0.9864813,0.004362626,0.001766999,0.001231077,0.005709331,0.0004485297],"domain_scores_gemma":[0.8621783,0.08937317,0.003566175,0.002789541,0.03534984,0.006743087],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002037345,0.000008805671,0.00001991834,0.0002547574,0.00003872276,0.00002240723,0.000006942197,0.00005144507,0.00001277059,0.0005773546,0.9900433,0.008943142],"study_design_scores_gemma":[0.0001427568,0.00005392836,0.0003526065,0.002090352,0.000197469,0.0002414616,0.00005555338,0.001509642,0.0001156065,0.01493664,0.9802209,0.00008311753],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002300956,0.02243311,0.0009556566,0.09994618,0.8754655,0.00001706353,0.00009976497,0.0001152178,0.0009445261],"genre_scores_gemma":[0.0004928723,0.01409409,0.0006394967,0.03317894,0.9471267,0.00003473206,0.0000705142,0.00008797345,0.004274821],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9773995,"threshold_uncertainty_score":0.1195243,"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."}}