{"id":"W3165472611","doi":"10.2139/ssrn.3309427","title":"Differential Treatment Benefit Prediction for Treatment Selection in Depression: A Deep Learning Analysis of STAR*D and CO-MED Data","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Treatment of Major Depression","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Differential treatment; Depression (economics); Selection (genetic algorithm); Star (game theory); Artificial intelligence; Psychology; Medicine; Computer science; Astrophysics; Economics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.004427382,0.000630071,0.001372597,0.001189478,0.0003350695,0.0009277323,0.001155086,0.001394292,0.003245539],"category_scores_gemma":[0.01555945,0.0002888586,0.001460372,0.0009248437,0.0005212079,0.0008617722,0.0008882894,0.002111734,0.0006205222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104939,"about_ca_system_score_gemma":0.001433699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090229,"about_ca_topic_score_gemma":0.01520364,"domain_scores_codex":[0.9989336,0.0005529362,0.00007525417,0.0001866236,0.0001151659,0.0001363803],"domain_scores_gemma":[0.9906715,0.007310182,0.0005139751,0.0006042999,0.0005052402,0.0003948558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007805852,0.003071088,0.5043148,0.0007133486,0.002207067,0.000608874,0.0001892009,0.2245591,0.001524044,0.005480853,0.05065127,0.1988746],"study_design_scores_gemma":[0.000342194,0.0005661111,0.06834149,0.0001103735,0.0004137207,0.0002013651,0.0001077693,0.91731,0.0007905443,0.008752594,0.003010016,0.00005384744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.95559,0.002535035,0.01792108,0.00662963,0.0001973052,0.0001209726,0.01426917,0.0003342181,0.002402546],"genre_scores_gemma":[0.9812332,0.0003412801,0.005832108,0.0004023696,0.00007540894,0.00005277336,0.01074446,0.00002966032,0.001288709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01090229,"threshold_uncertainty_score":0.02341455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02199220800272611,"score_gpt":0.3123456822692599,"score_spread":0.2903534742665337,"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."}}