{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006759421,0.0003238509,0.001065358,0.0003194714,0.00008745068,0.00002004307,0.0002086368,0.0002103144,0.00109577],"category_scores_gemma":[0.005045131,0.0001694839,0.0001546653,0.0004047208,0.0001338688,0.0001576061,0.00006319956,0.0005703328,0.00002387747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007327196,"about_ca_system_score_gemma":0.0002270803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000237356,"about_ca_topic_score_gemma":0.000002245639,"domain_scores_codex":[0.9973115,0.00004729007,0.0009127434,0.0002784291,0.001074815,0.0003752782],"domain_scores_gemma":[0.9974143,0.0001693792,0.0003127725,0.0002735667,0.0004344594,0.001395514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006003355,0.002087506,0.6616496,0.0001993013,0.0004984613,0.001006064,0.004301368,0.000001607572,0.01060898,0.0002572233,0.01781332,0.3009762],"study_design_scores_gemma":[0.007311442,0.04929991,0.9243978,0.001778018,0.0003061024,0.0003678333,0.001431865,0.00005959026,0.002243008,0.0006752659,0.01172181,0.0004073256],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8876395,0.001625319,0.0001988177,0.1084593,0.0009657228,0.0004072477,0.000002236335,0.00002768608,0.0006742046],"genre_scores_gemma":[0.9876447,0.0001680677,0.002424908,0.008606508,0.0005170162,0.000003177296,0.000001875935,0.00003198068,0.0006018009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3005689,"threshold_uncertainty_score":0.9998174,"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."}}