{"id":"W2138860112","doi":"10.1002/jhm.399","title":"Medical admission order sets to improve deep vein thrombosis prophylaxis rates and other outcomes","year":2009,"lang":"en","type":"article","venue":"Journal of Hospital Medicine","topic":"Hospital Admissions and Outcomes","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; Trillium Health Centre","funders":"","keywords":"Medicine; Deep vein; Hospital medicine; Thrombosis; Emergency medicine; Venous thrombosis; Psychological intervention; Pediatrics; Internal medicine; Nursing","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":[0.001650268,0.0003782894,0.0004734698,0.0009311386,0.0003009378,0.001041906,0.0006413425,0.0005010585,0.00614908],"category_scores_gemma":[0.02097146,0.000167109,0.0006873272,0.001009379,0.0002768106,0.0005827375,0.0005827864,0.00108945,0.0003887104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364084,"about_ca_system_score_gemma":0.002337086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002373152,"about_ca_topic_score_gemma":0.002795645,"domain_scores_codex":[0.997744,0.0009893965,0.0003254678,0.0001516614,0.0005210979,0.0002685003],"domain_scores_gemma":[0.9833655,0.00669405,0.006134553,0.0005293377,0.0005881503,0.002688394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01299503,0.02340186,0.4780199,0.001293469,0.0008165557,0.0001608745,0.0004340832,0.00318382,0.001284012,0.0006159416,0.01279921,0.4649953],"study_design_scores_gemma":[0.002807709,0.02008178,0.9622061,0.0006935803,0.0006036145,0.0002939648,0.0003077456,0.005384415,0.0018351,0.001075869,0.00464365,0.00006642023],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888271,0.003011999,0.0007263029,0.002214276,0.0002394254,0.0002767179,0.0005229891,0.0003000603,0.00388117],"genre_scores_gemma":[0.9952946,0.0008192915,0.002118944,0.0005135275,0.0001575041,0.0001351341,0.0005319145,0.00001580728,0.000413294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00614908,"threshold_uncertainty_score":0.02057076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144635141979308,"score_gpt":0.3264394971110702,"score_spread":0.3149931456912771,"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."}}