{"id":"W2997759399","doi":"10.1055/s-0039-3400303","title":"Development of a Clinical Prediction Rule for Venous Thromboembolism in Patients with Acute Leukemia","year":2020,"lang":"en","type":"article","venue":"Thrombosis and Haemostasis","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Acute leukemia; Internal medicine; Myeloid leukemia; Leukemia; Retrospective cohort study; Cumulative incidence; Logistic regression; Incidence (geometry); Surgery; Cohort","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002514524,0.0005897018,0.0008597641,0.002395391,0.0003849421,0.001294503,0.0006867072,0.0005126792,0.0008592764],"category_scores_gemma":[0.0135281,0.0002140238,0.0006101801,0.00103112,0.0002625425,0.000416536,0.0005783629,0.0008603873,0.0003910593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004852911,"about_ca_system_score_gemma":0.001127054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004032644,"about_ca_topic_score_gemma":0.004477589,"domain_scores_codex":[0.9984863,0.0005358058,0.0002709139,0.0001570396,0.000455844,0.00009405833],"domain_scores_gemma":[0.9926912,0.004068432,0.0009679237,0.0002079249,0.001687155,0.0003773668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003048429,0.0001151009,0.9663635,0.00003006087,0.00009295924,0.0001474509,0.00003007458,0.004975204,0.0003013839,0.0001507597,0.001830911,0.02565788],"study_design_scores_gemma":[0.0002452246,0.0006986191,0.5080259,0.0001770012,0.000387771,0.001729017,0.0003445083,0.4804142,0.003377606,0.001973722,0.002581764,0.00004463772],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587512,0.0005902811,0.03440883,0.0008404281,0.0001508564,0.0002567599,0.001894361,0.0004150228,0.002692214],"genre_scores_gemma":[0.9840378,0.000107891,0.01412944,0.00005800061,0.00005838687,0.00006975076,0.001295775,0.000007539134,0.000235432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004032644,"threshold_uncertainty_score":0.01329827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07321084531439667,"score_gpt":0.3382193074732771,"score_spread":0.2650084621588804,"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."}}