{"id":"W4388981823","doi":"10.2196/49007","title":"Additional Value From Free-Text Diagnoses in Electronic Health Records: Hybrid Dictionary and Machine Learning Classification Study","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitätsspital Zürich; Universität Zürich","keywords":"Preprint; Health records; Medical diagnosis; Electronic health record; Value (mathematics); Computer science; Medicine; World Wide Web; Health care; Radiology","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":[0.006378518,0.0003657772,0.0006113889,0.004101185,0.0003543218,0.002006049,0.0006971127,0.0007926943,0.0024596],"category_scores_gemma":[0.05018208,0.0001917186,0.001015053,0.003647255,0.0007275022,0.00268394,0.001334586,0.0007592602,0.0005438054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000675482,"about_ca_system_score_gemma":0.0006340119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001538772,"about_ca_topic_score_gemma":0.0018422,"domain_scores_codex":[0.994496,0.002911501,0.0007744215,0.0007268595,0.0008870335,0.0002042142],"domain_scores_gemma":[0.8990823,0.08523108,0.006946992,0.003581046,0.004224282,0.0009343319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002003524,0.000641174,0.924813,0.0003424797,0.0005123246,0.0003394225,0.0008327893,0.00158789,0.0008634277,0.0003337401,0.0004894491,0.06724072],"study_design_scores_gemma":[0.0002360789,0.002088955,0.9060232,0.0002598263,0.0008167516,0.002332893,0.002843199,0.08010343,0.001780718,0.001883557,0.001554699,0.00007669572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952554,0.0003693627,0.002720556,0.0001472512,0.00001696853,0.00006526116,0.0006446828,0.00002212474,0.0007583538],"genre_scores_gemma":[0.996253,0.000144208,0.002388167,0.00003990798,0.00003459243,0.00003003849,0.0009173046,0.00000899512,0.0001837136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006378518,"threshold_uncertainty_score":0.03373325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05315777442848343,"score_gpt":0.4041413538563754,"score_spread":0.3509835794278919,"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."}}