{"id":"W2888250172","doi":"10.1111/bjh.15533","title":"Predictive value of venous thromboembolism (<scp>VTE</scp>)‐<scp>BLEED</scp> to predict major bleeding and other adverse events in a practice‐based cohort of patients with <scp>VTE</scp>: results of the <scp>XALIA</scp> study","year":2018,"lang":"en","type":"article","venue":"British Journal of Haematology","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Bundesministerium für Bildung und Forschung","keywords":"Medicine; Bleed; Interquartile range; Hazard ratio; Internal medicine; Prospective cohort study; Confidence interval; Rivaroxaban; Incidence (geometry); Cohort; Anticoagulant; Adverse effect; Warfarin; Surgery; Atrial fibrillation","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":[0.002449695,0.0004404742,0.0005563712,0.000725891,0.0002420518,0.001141017,0.0005825773,0.0009271319,0.0008744127],"category_scores_gemma":[0.007573366,0.0004023744,0.0008150028,0.0009757469,0.0004026313,0.000571305,0.0005614921,0.001342088,0.0002406686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004112077,"about_ca_system_score_gemma":0.0004154243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002682932,"about_ca_topic_score_gemma":0.002565178,"domain_scores_codex":[0.9987844,0.0005017652,0.0001447203,0.0002641995,0.0002104645,0.000094561],"domain_scores_gemma":[0.9950493,0.001631336,0.001687467,0.0005225671,0.0003686745,0.0007406169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004715066,0.0000426168,0.9981316,0.000007614808,0.0001795314,0.00002655658,0.00002262679,0.0001449692,0.00007528781,0.00002098604,0.0001042823,0.0007726004],"study_design_scores_gemma":[0.0002286953,0.0004712138,0.9950945,0.00001077107,0.0002064489,0.0002705411,0.00005869405,0.003211761,0.00009862513,0.0001078591,0.0002302956,0.00001058335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988195,0.0003538874,0.0001224316,0.00006892368,0.000009966133,0.00001497278,0.0003650141,0.00000419596,0.0002409434],"genre_scores_gemma":[0.9991589,0.00006637493,0.0001278237,0.00002596297,0.00001831634,0.000007831271,0.000543865,0.000001596159,0.00004943082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002682932,"threshold_uncertainty_score":0.01295537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009358130126132092,"score_gpt":0.2605367834175638,"score_spread":0.2511786532914317,"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."}}