{"id":"W3156664080","doi":"10.46747/cfp.6704303","title":"Optimizing handover for family medicine outpatients using an electronic medical record–integrated tool","year":2021,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Hospital Admissions and Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of Family Physicians of Canada; University of Toronto; McMaster University","funders":"","keywords":"Handover; Electronic medical record; Process (computing); Medical record; Medicine; Computer science; Family medicine; Continuity of care; Telecommunications; Health care; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0047233,0.0003676419,0.0004496653,0.001640448,0.0009167407,0.002131192,0.0005951622,0.0004380832,0.003194804],"category_scores_gemma":[0.03195405,0.0001645244,0.0004568715,0.001381254,0.0001543886,0.001229202,0.001117079,0.0006967912,0.0007953505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002391366,"about_ca_system_score_gemma":0.005576378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0377195,"about_ca_topic_score_gemma":0.09660427,"domain_scores_codex":[0.9952697,0.002038748,0.0007501288,0.0003082074,0.001323335,0.0003098469],"domain_scores_gemma":[0.9868785,0.004739447,0.002998421,0.0005947757,0.003263691,0.001525192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005362743,0.0008742287,0.2414115,0.0009179303,0.0001909583,0.0003403945,0.002603282,0.001173115,0.0009102217,0.0004377883,0.03353597,0.7170683],"study_design_scores_gemma":[0.0004531702,0.001554159,0.8921009,0.004247281,0.0005188744,0.001042552,0.007880511,0.01214982,0.003033414,0.001186238,0.07550941,0.0003237076],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8592801,0.01019137,0.03200499,0.02899224,0.001155618,0.003284382,0.008672554,0.002991295,0.05342741],"genre_scores_gemma":[0.9007228,0.00513635,0.08438169,0.001773379,0.0004962955,0.0006709202,0.003405774,0.0001192811,0.003293518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0377195,"threshold_uncertainty_score":0.07499987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03261296776024003,"score_gpt":0.290989903725108,"score_spread":0.258376935964868,"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."}}