{"id":"W2071516670","doi":"10.12927/hcq.2010.21974","title":"Optimizing Physician Handover Through the Creation of a Comprehensive Minimum Data Set","year":2010,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Hospital Admissions and Outcomes","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Handover; Duration (music); Best practice; Set (abstract data type); Consistency (knowledge bases); Health care; Patient safety; Service (business); Accountability; Process (computing); Medicine; Nursing; Medical emergency; Business; Process management; Computer science; Marketing","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":[0.06287908,0.00083786,0.001210879,0.008565592,0.002213769,0.007221777,0.001999537,0.0008055496,0.001459878],"category_scores_gemma":[0.16871,0.0008584232,0.001407706,0.006480574,0.0008517129,0.007059586,0.007496906,0.001675103,0.0007004808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005209368,"about_ca_system_score_gemma":0.01836179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008390159,"about_ca_topic_score_gemma":0.01285361,"domain_scores_codex":[0.9485712,0.02638332,0.01025418,0.003233051,0.01018586,0.001372382],"domain_scores_gemma":[0.8491338,0.05832542,0.02397924,0.018327,0.04484481,0.005389681],"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":[0.0005367498,0.001088157,0.2221944,0.002232683,0.0003086335,0.0003600784,0.02177781,0.01619512,0.007363764,0.006778337,0.01132263,0.7098416],"study_design_scores_gemma":[0.0006479332,0.004697436,0.4611125,0.006301025,0.0007637686,0.001230156,0.09091984,0.1692151,0.04010146,0.028096,0.1957957,0.001119022],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5693675,0.001429866,0.3880506,0.009333172,0.0003727662,0.009258113,0.005065063,0.002515538,0.01460743],"genre_scores_gemma":[0.3155639,0.0004750406,0.6751174,0.0003373762,0.00007310996,0.002132962,0.005102139,0.0001350592,0.001062939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06287908,"threshold_uncertainty_score":0.3325403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05137052042813931,"score_gpt":0.3636222187591936,"score_spread":0.3122516983310543,"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."}}