{"id":"W2007387322","doi":"10.1186/1472-6947-10-44","title":"Speech recognition software and electronic psychiatric progress notes: physicians' ratings and preferences","year":2010,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Workflow; Documentation; Usability; Context (archaeology); Health information technology; Health informatics; Health care; Mental health; Quality (philosophy); Medicine; Computer science; Medical education; Nursing; Psychiatry; Public health; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009963272,0.0001591479,0.0002209179,0.001127011,0.0005007664,0.001568499,0.0002857042,0.0006824099,0.003566889],"category_scores_gemma":[0.07646575,0.0001814458,0.00036532,0.0006825195,0.0008108647,0.001167449,0.001020831,0.0006073661,0.0004607223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006392892,"about_ca_system_score_gemma":0.0006952752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00199693,"about_ca_topic_score_gemma":0.003261513,"domain_scores_codex":[0.990751,0.004881615,0.001182595,0.0005188688,0.002242317,0.0004236459],"domain_scores_gemma":[0.914188,0.05749438,0.01578485,0.001159348,0.007367834,0.004005675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001522621,0.0003878645,0.8877774,0.0004307867,0.0001124188,0.0005517797,0.03886318,0.0003530415,0.002658184,0.0001597394,0.001744866,0.06543805],"study_design_scores_gemma":[0.0001507457,0.003301848,0.895862,0.0003430968,0.00009084928,0.002312511,0.0890507,0.001983484,0.001529577,0.0002816747,0.004970187,0.0001233003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975249,0.0003065211,0.0003106381,0.0003844673,0.00001345955,0.00003339916,0.00005309406,0.000007689548,0.001365828],"genre_scores_gemma":[0.9983944,0.0002351752,0.0007196135,0.0001634345,0.00001697294,0.00002522305,0.00005495315,0.000005129957,0.0003850781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009963272,"threshold_uncertainty_score":0.05269146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819613752137532,"score_gpt":0.4169977288422666,"score_spread":0.3688015913208913,"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."}}