{"id":"W2751143095","doi":"10.2196/resprot.7757","title":"Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods","year":2017,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Big data; Artificial intelligence; Machine learning; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02519361,0.001790686,0.0009449846,0.002612062,0.001503264,0.004971981,0.00523555,0.003023674,0.006984829],"category_scores_gemma":[0.05764671,0.001672862,0.001897309,0.002480493,0.004410337,0.005912019,0.007410512,0.005548738,0.003109632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002063147,"about_ca_system_score_gemma":0.009343815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917612,"about_ca_topic_score_gemma":0.003022357,"domain_scores_codex":[0.9864643,0.006985605,0.0007321587,0.00153499,0.003840253,0.0004427515],"domain_scores_gemma":[0.9640568,0.02034028,0.001449452,0.004749063,0.008244336,0.00116007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003032911,0.0009753119,0.01470578,0.001139932,0.0002668309,0.000612357,0.0007989604,0.1001303,0.004070005,0.5453426,0.02655119,0.3051034],"study_design_scores_gemma":[0.0001367322,0.0001435944,0.0007786491,0.0002486487,0.00006438101,0.0002891808,0.0001896491,0.7257549,0.004394493,0.2438976,0.02402567,0.00007647899],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.0009642291,0.0001594756,0.9937978,0.002528117,0.00008007702,0.0005218554,0.00012058,0.0002811328,0.001546572],"genre_scores_gemma":[0.03637023,0.0004068927,0.9586278,0.0006179141,0.0002814424,0.001672559,0.0004490247,0.0001384812,0.001435689],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.02519361,"threshold_uncertainty_score":0.1332382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8694162831942269,"score_gpt":0.7297005020872908,"score_spread":0.1397157811069362,"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."}}