{"id":"W3109658708","doi":"10.1016/s2542-4513(20)30516-2","title":"How to treat venous thromboembolism (TVE) in cancer patients: ten years of multidisciplinary team meetings (MDTM) at Saint-Louis Hospital","year":2020,"lang":"en","type":"article","venue":"JMV-Journal de Médecine Vasculaire","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Pulmonary embolism; Deep vein; Cancer; Thrombosis; Venous thromboembolism; Venous thrombosis; Multidisciplinary team; Breast cancer; Multidisciplinary approach; Anticoagulant therapy; Internal medicine","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":[0.002621512,0.0003221618,0.0002809863,0.0004558949,0.003678581,0.002541813,0.0009607066,0.002018753,0.004822379],"category_scores_gemma":[0.0065525,0.0004768003,0.0004778777,0.000386897,0.0005571868,0.001441946,0.002932784,0.004289328,0.0006908993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004532842,"about_ca_system_score_gemma":0.01647711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02510506,"about_ca_topic_score_gemma":0.1031191,"domain_scores_codex":[0.9976844,0.0009645907,0.0001596332,0.0001981356,0.0003652402,0.000628007],"domain_scores_gemma":[0.9888096,0.0006930546,0.0007422262,0.00007966824,0.001049703,0.008625763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000401301,0.004266048,0.2231084,0.001007849,0.0003144952,0.005601839,0.01300802,0.001150248,0.002425765,0.0008792864,0.2765455,0.4712912],"study_design_scores_gemma":[0.0004724124,0.002074945,0.6051071,0.004368418,0.0002265786,0.005414461,0.05849342,0.001516849,0.0009417352,0.001791893,0.3193045,0.0002876704],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4013364,0.04263134,0.001671926,0.5113744,0.008991416,0.0004425907,0.0003058825,0.0002523629,0.03299376],"genre_scores_gemma":[0.8350817,0.03554324,0.009377606,0.09094926,0.005561756,0.0003582323,0.0006247089,0.0001719241,0.02233158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02510506,"threshold_uncertainty_score":0.04991788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0115383838594497,"score_gpt":0.2566358387072761,"score_spread":0.2450974548478264,"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."}}