{"id":"W4289730999","doi":"10.3389/fdgth.2022.932411","title":"An integration engineering framework for machine learning in healthcare","year":2022,"lang":"en","type":"article","venue":"Frontiers in Digital Health","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Canadian Institute for Advanced Research; University of Toronto; Centre for Global Health Research; Hospital for Sick Children; Public Health Ontario","funders":"","keywords":"System integration; Computer science; Health care; Domain (mathematical analysis); Artificial intelligence; Software engineering; Systems engineering; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005761069,0.0001129815,0.0002800444,0.0003918478,0.0001615996,0.00002974697,0.00008659365,0.00006867822,0.0000102199],"category_scores_gemma":[0.0004417369,0.000126953,0.00004285095,0.0005075654,0.00001429433,0.0002293394,0.00001875615,0.0007641353,0.000001345204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117092,"about_ca_system_score_gemma":0.0004841459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001531324,"about_ca_topic_score_gemma":0.0002137631,"domain_scores_codex":[0.9985669,0.00005001135,0.0005070218,0.0002794528,0.0001857599,0.0004108213],"domain_scores_gemma":[0.9993891,0.0001105595,0.00009795258,0.0001666313,0.00004800606,0.0001877519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003730377,0.0002985465,0.4554243,0.0003321348,0.000004200804,0.000005493964,0.004943971,0.004356383,0.000004049,0.003137799,0.000673466,0.5304466],"study_design_scores_gemma":[0.0007422228,0.010533,0.05141899,0.001148677,0.0000105324,0.00006906766,0.04985168,0.7618623,0.0003204898,0.09863494,0.02458588,0.0008222247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6584913,0.00422166,0.300523,0.03021475,0.003618316,0.00254139,0.0001020043,0.0002177304,0.00006989354],"genre_scores_gemma":[0.977684,0.00008665608,0.01990241,0.001335375,0.0001552199,0.0002487446,0.0004972902,0.00002995138,0.00006032522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7575059,"threshold_uncertainty_score":0.5176994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05817850833940544,"score_gpt":0.3868554759883091,"score_spread":0.3286769676489036,"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."}}