{"id":"W4296523277","doi":"10.2196/37833","title":"Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institute of Neurological Disorders and Stroke; Agency for Healthcare Research and Quality; Cincinnati Children's Hospital Medical Center","keywords":"Clinical decision support system; Software deployment; Artificial intelligence; Emergency department; Computer science; Health care; Certification; Identification (biology); Machine learning; Decision support system; Medicine; Knowledge management; Nursing; Software engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002641756,0.00006471235,0.0001843349,0.00008328527,0.0002014003,0.000009221161,0.00005169276,0.00004619224,0.0002200851],"category_scores_gemma":[0.001083823,0.00005688181,0.00002850343,0.000131577,0.0000330232,0.0001348476,0.00006654541,0.0002870683,0.000003292694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005459451,"about_ca_system_score_gemma":0.0005196026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007988935,"about_ca_topic_score_gemma":0.00001890267,"domain_scores_codex":[0.9978487,0.00009774406,0.001261511,0.00007270154,0.0006000632,0.0001192221],"domain_scores_gemma":[0.9986297,0.0005513293,0.0003722476,0.00008419118,0.0002341588,0.0001283912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001918146,0.0006387887,0.2017523,0.0002616959,0.00004853307,0.000001432595,0.04787273,0.000007612076,0.000002592716,0.00008192694,0.001090265,0.7480503],"study_design_scores_gemma":[0.001334334,0.005108906,0.02617323,0.00006514157,0.000172039,0.00008276133,0.7427974,0.01850049,0.001624268,0.0001000511,0.203837,0.0002043569],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942604,0.00005927772,0.002586933,0.001506941,0.0002427478,0.001235569,0.000003093106,0.00002239416,0.00008261916],"genre_scores_gemma":[0.9900068,0.00006736931,0.008438282,0.0008005562,0.000131981,0.0003247362,0.0001704611,0.000007372489,0.00005240813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7478459,"threshold_uncertainty_score":0.2409778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2412855034647876,"score_gpt":0.5724309039196083,"score_spread":0.3311454004548207,"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."}}