{"id":"W4327575299","doi":"10.1136/bmjoq-2022-001984","title":"Computerised clinical decision support system for the diagnosis of pulmonary thromboembolism: a preclinical pilot study","year":2023,"lang":"en","type":"article","venue":"BMJ Open Quality","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Government of Canada; Government of Alberta","keywords":"Medicine; Intensive care medicine; Decision support system; Clinical decision support system; Venous thromboembolism; Internal medicine; Computer science; Thrombosis; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.01804828,0.0002818005,0.00218949,0.00009651731,0.0002759217,0.0001072187,0.001103792,0.0001079094,0.0001490278],"category_scores_gemma":[0.001956729,0.00018656,0.0004084723,0.0005049561,0.0001752205,0.0001391215,0.001608899,0.0002427421,0.0001549751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000639982,"about_ca_system_score_gemma":0.0002489983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000811666,"about_ca_topic_score_gemma":0.0001252224,"domain_scores_codex":[0.9943081,0.0009133578,0.002670007,0.0008222515,0.0008364452,0.000449898],"domain_scores_gemma":[0.9897478,0.007120039,0.000842602,0.001754136,0.0003074709,0.0002279781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005960971,0.02706203,0.5552515,0.001661975,0.002037322,0.0001608216,0.0009889398,0.00005494879,0.00001818338,0.002881557,0.1679645,0.2359572],"study_design_scores_gemma":[0.005141804,0.006158434,0.9773992,0.0003931847,0.0007794191,0.000008036303,0.003100407,0.001262635,0.00002884794,0.0002187328,0.005249592,0.0002597587],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652395,0.00005313202,0.001457102,0.002728349,0.001847256,0.02667898,0.0001264686,0.0002068144,0.001662431],"genre_scores_gemma":[0.9917914,0.0001817518,0.001125137,0.0008244735,0.0004870662,0.005277331,0.00007260202,0.00005090341,0.0001893526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4221476,"threshold_uncertainty_score":0.7607697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3659672994914377,"score_gpt":0.5379070115989406,"score_spread":0.1719397121075029,"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."}}