{"id":"W2951857323","doi":"10.1097/01.hs9.0000564816.09273.68","title":"S1642 DEVELOPMENT OF A CLINICAL PREDICTION RULE FOR VENOUS THROMBOEMBOLISM IN PATIENTS WITH ACUTE LEUKEMIA","year":2019,"lang":"en","type":"article","venue":"HemaSphere","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Medicine; Interquartile range; Pulmonary embolism; Internal medicine; Thrombosis; Acute leukemia; Venous thrombosis; Deep vein; Retrospective cohort study; Myeloid leukemia; Logistic regression; Surgery; Leukemia","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002926912,0.0001698213,0.0008897896,0.00005636943,0.00003728383,0.000007294835,0.0000907885,0.0001305277,0.000197595],"category_scores_gemma":[0.00002645394,0.0001339289,0.0001006577,0.0001420496,0.00003570507,0.00008180999,0.00005468925,0.0001428348,0.00005132211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000154986,"about_ca_system_score_gemma":0.0003770482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002457715,"about_ca_topic_score_gemma":0.00003630704,"domain_scores_codex":[0.9983202,0.0000216372,0.0006852393,0.0003535869,0.0003304195,0.0002889385],"domain_scores_gemma":[0.999175,0.00005085393,0.0002082118,0.0003297607,0.0001395319,0.00009668384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001257794,0.004976712,0.9407709,0.0009649505,0.001083017,0.00001151242,0.001610527,0.00008153787,0.0001262954,0.0006030322,0.004490857,0.04402283],"study_design_scores_gemma":[0.007379299,0.001611486,0.9824352,0.0004237219,0.0002221889,0.000001247198,0.0001721614,0.0001038018,0.0004672848,0.00005303595,0.006989469,0.0001410961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935648,0.00005071263,0.0002545338,0.00005367353,0.000305587,0.001999296,0.00001899804,0.00003913412,0.003713207],"genre_scores_gemma":[0.9886,0.00002670312,0.0103663,0.0002015349,0.00007547096,0.0001355131,0.0001254848,0.00003931961,0.0004297041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04388173,"threshold_uncertainty_score":0.5461463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01625241081758144,"score_gpt":0.2907961034065933,"score_spread":0.2745436925890119,"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."}}