{"id":"W4387914853","doi":"10.2196/49886","title":"A Large Language Model Screening Tool to Target Patients for Best Practice Alerts: Development and Validation","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Best practice; Medical prescription; Deep vein; Health care; Medical emergency; Population; Diagnosis code; Intensive care medicine; Emergency department; Emergency medicine; Thrombosis; Surgery; Nursing","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":[0.001128932,0.0001179279,0.0001412554,0.0001457121,0.0001963725,0.0001187757,0.0003929953,0.0001040318,0.000006420461],"category_scores_gemma":[0.001939655,0.0001057827,0.00002077164,0.000362732,0.00001147444,0.0007695445,0.0004661172,0.0002180021,0.00008202926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000042038,"about_ca_system_score_gemma":0.0001734008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004646507,"about_ca_topic_score_gemma":0.000002349521,"domain_scores_codex":[0.9981347,0.00003814782,0.0005054566,0.0001387869,0.0008130405,0.0003698398],"domain_scores_gemma":[0.9988494,0.0003096782,0.0001521393,0.0002428773,0.0001729909,0.000272907],"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":[0.00004657267,0.000275302,0.002989977,0.001270959,0.0000448291,0.00001555943,0.291225,0.005009008,0.000001759586,0.01104511,0.0230532,0.6650227],"study_design_scores_gemma":[0.0005246691,0.00009181796,0.0003654357,0.0001104362,0.000002451682,0.000005144845,0.001668625,0.9299913,0.00003086068,0.00006418281,0.06699733,0.0001477435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1465597,0.000006371781,0.8503242,0.001707469,0.0001025786,0.0006397373,0.00001147413,0.0002066467,0.0004418654],"genre_scores_gemma":[0.0631687,0.000005078329,0.9305792,0.005527106,0.00005480969,0.0002981797,0.0001705143,0.00001445993,0.0001819584],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9249823,"threshold_uncertainty_score":0.4313692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02960621836339888,"score_gpt":0.3537486169459002,"score_spread":0.3241423985825013,"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."}}