{"id":"W4281976759","doi":"10.3233/shti220140","title":"Implementing Predictive Models Within an Electronic Health Record System: Lessons from an External Validation of a Suicide Risk Model","year":2022,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Island Health; University Health Network; Centre for Addiction and Mental Health","funders":"Centre for Addiction and Mental Health","keywords":"Documentation; Context (archaeology); Computer science; Sample (material); Predictive modelling; Model validation; Data science; Data mining; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.004170117,0.0001812389,0.00053978,0.0006384716,0.001226544,0.0000186763,0.0006857203,0.00008336981,9.07768e-7],"category_scores_gemma":[0.0001189529,0.0001851568,0.00002314285,0.0007395361,0.0001244084,0.0008023409,0.001049527,0.001153669,2.363325e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007548544,"about_ca_system_score_gemma":0.0007021911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003294137,"about_ca_topic_score_gemma":0.001244018,"domain_scores_codex":[0.9965099,0.0005688908,0.00155071,0.0003012206,0.000322691,0.0007466386],"domain_scores_gemma":[0.9973831,0.0001358098,0.001666286,0.0006036805,0.0001226631,0.00008849312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005312271,0.00008947815,0.05074334,0.001429304,0.00006519082,0.000001405029,0.1378326,0.4432274,0.000001280124,0.3053267,0.0000236692,0.06120653],"study_design_scores_gemma":[0.0003404866,0.001497967,0.0006021765,0.0001745272,0.000004590248,0.00001554051,0.03282345,0.8943725,0.00001077444,0.07002749,0.00001784731,0.0001126408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5369875,0.00231103,0.4572009,0.002314517,0.0001834431,0.0006208466,0.00008261098,0.0002783726,0.00002082417],"genre_scores_gemma":[0.9132459,0.00109404,0.08510534,0.0003483679,0.00001228779,0.0001619129,0.00002009076,0.00001018554,0.000001931777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4511451,"threshold_uncertainty_score":0.9433708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0572913661815416,"score_gpt":0.3888787894245317,"score_spread":0.3315874232429902,"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."}}