{"id":"W2744939501","doi":"10.2196/medinform.7627","title":"Clinical Note Creation, Binning, and Artificial Intelligence","year":2017,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Computer science; Function (biology); Data science; Software; Artificial intelligence; Database","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005030316,0.0001558086,0.0004413719,0.00007541012,0.001686733,0.00005597878,0.0005477751,0.0006952704,0.0006444149],"category_scores_gemma":[0.004923977,0.0001228586,0.00005505437,0.00007002836,0.0004698398,0.0003620105,0.0003103706,0.001784793,0.001178588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001165272,"about_ca_system_score_gemma":0.001548188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001912736,"about_ca_topic_score_gemma":0.0003219102,"domain_scores_codex":[0.9956736,0.0003271913,0.002462946,0.0001456823,0.0006941478,0.000696424],"domain_scores_gemma":[0.996071,0.00116358,0.001098227,0.0007136656,0.0002000765,0.0007534781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006160216,0.0001021698,0.08371453,0.001366859,0.0000286479,0.000009632563,0.01628623,3.688727e-7,0.000001225975,0.03461369,0.02458235,0.8392327],"study_design_scores_gemma":[0.001329887,0.0007452866,0.06282718,0.003234773,0.00004233315,0.00003845895,0.01069128,0.1058133,0.00001807554,0.01332558,0.8012168,0.0007170125],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.765395,0.0002079914,0.07303533,0.02202241,0.007312817,0.003964648,0.00002210823,0.00047188,0.1275678],"genre_scores_gemma":[0.9813324,0.0007715359,0.004555522,0.007890686,0.00307797,0.0003362322,0.00002244131,0.00003795357,0.001975256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8385156,"threshold_uncertainty_score":0.9996129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1513405335275942,"score_gpt":0.5670605840010884,"score_spread":0.4157200504734941,"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."}}