{"id":"W2893472280","doi":"10.1016/j.cjca.2018.07.470","title":"IMPLEMENTING A PRE AND POST CHECKLIST: REDUCING LENGTH OF STAY AND READMISSION RATES FOR AN IN-HOSPITAL CARDIOLOGY UNIT","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Emissions Reduction Alberta","funders":"","keywords":"Medicine; Checklist; Psychological intervention; Demographics; Hospital discharge; Discharge planning; Emergency medicine; Community hospital; Medical emergency; Coronary care unit; Transitional care; Intensive care medicine; Health care; Nursing; Internal medicine; Myocardial infarction","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":[0.004596177,0.001024342,0.0008298703,0.001150079,0.002450324,0.001266724,0.001817717,0.001447228,0.004195517],"category_scores_gemma":[0.03599522,0.0006121362,0.001314194,0.0004976941,0.0004282384,0.001265535,0.00252293,0.00254824,0.0004823483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00242809,"about_ca_system_score_gemma":0.01444397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01078266,"about_ca_topic_score_gemma":0.0320311,"domain_scores_codex":[0.9956937,0.001647729,0.0007437984,0.0002667774,0.0009292765,0.0007187394],"domain_scores_gemma":[0.9679533,0.006059607,0.008081815,0.0009450496,0.004390683,0.01256943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.003357701,0.03036127,0.562637,0.001668127,0.0006868624,0.0008581156,0.003121395,0.0009594586,0.002413968,0.0001794808,0.03024128,0.3635154],"study_design_scores_gemma":[0.0008710681,0.01206874,0.9750725,0.001092097,0.0003504552,0.0004040264,0.004823723,0.001265796,0.0006515157,0.0001643629,0.003083409,0.0001522564],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840882,0.001015523,0.001390232,0.005901736,0.001077474,0.001621513,0.0003115239,0.0003368874,0.00425692],"genre_scores_gemma":[0.9775039,0.001019496,0.01375623,0.003409862,0.0005824211,0.001165721,0.0005729681,0.00004434767,0.001945033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01078266,"threshold_uncertainty_score":0.02430719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04190963627232448,"score_gpt":0.4125412402673274,"score_spread":0.3706316039950029,"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."}}