{"id":"W2995419762","doi":"10.2196/14487","title":"Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emergency department; Medical emergency; Medical record; Retrospective cohort study; Health records; Medicine; Computer science; Health care; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002677651,0.000263783,0.0003868939,0.001829285,0.0005672719,0.000815795,0.0005061352,0.0005395748,0.002016751],"category_scores_gemma":[0.01171805,0.0004642079,0.0005647584,0.001800652,0.0005244311,0.00124998,0.0007244052,0.0006288254,0.0003888707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005843118,"about_ca_system_score_gemma":0.0007064288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147876,"about_ca_topic_score_gemma":0.003316687,"domain_scores_codex":[0.9974505,0.0008022917,0.000520388,0.0004885065,0.0004611433,0.0002772649],"domain_scores_gemma":[0.989251,0.003464034,0.004894934,0.0005248265,0.001304891,0.0005602879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007059116,0.0001189601,0.9958009,0.00007710054,0.00003829244,0.0001188033,0.001658645,0.00002133272,0.0001409798,0.00003031395,0.0001620099,0.001762108],"study_design_scores_gemma":[0.00001098079,0.0003263236,0.9907846,0.00005196072,0.00004685261,0.0005115566,0.00714741,0.0002648292,0.0001014865,0.00002625938,0.0007079322,0.00001978378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989012,0.0001471035,0.000206181,0.00003728721,0.000004112582,0.00006587132,0.0003878917,0.000002900356,0.000247333],"genre_scores_gemma":[0.9988465,0.0001475121,0.0002879877,0.00008316261,0.00001160049,0.0001173872,0.0003387478,0.000003860218,0.0001630905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003147876,"threshold_uncertainty_score":0.01416093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05602409849606121,"score_gpt":0.4907173656823114,"score_spread":0.4346932671862502,"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."}}