{"id":"W4415735130","doi":"10.1182/bloodadvances.2025017862","title":"Derivation and external validation of a venous thromboembolism risk prediction model in asparaginase-treated ALL","year":2025,"lang":"en","type":"article","venue":"Blood Advances","topic":"Acute Lymphoblastic Leukemia research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Daiichi Sankyo Europe; Gilead Sciences; Servier; LEO Pharma; National Cancer Institute; Regeneron Pharmaceuticals; National Institutes of Health; Novo Nordisk; Swedish Orphan Biovitrum; Astellas Pharma; Seagen; Pfizer; Incyte; MorphoSys; Celgene; Alexion Pharmaceuticals; Jazz Pharmaceuticals; Teva Pharmaceutical Industries; Syndax Pharmaceuticals; BeiGene; Sanofi; Amgen; National Heart, Lung, and Blood Institute; Eli Lilly and Company","keywords":"Derivation; Confidence interval; Venous thromboembolism; Proportional hazards model; Cohort; Retrospective cohort study; Cohort study; Risk assessment; Pulmonary embolism","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001555971,0.00009221605,0.0002383184,0.0002062286,0.00003103958,0.00000905652,0.00004881674,0.00006645958,0.000004635009],"category_scores_gemma":[0.0001807826,0.00008263071,0.00002120958,0.0002439,0.00006901654,0.0001952698,0.00003150252,0.0001177323,0.000001164462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009525858,"about_ca_system_score_gemma":0.0001586987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000153213,"about_ca_topic_score_gemma":0.00001468918,"domain_scores_codex":[0.9991359,0.00004127184,0.0002522953,0.0002078594,0.000212872,0.0001497984],"domain_scores_gemma":[0.9995466,0.00008454257,0.0000934881,0.0001406996,0.00009437458,0.00004031233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001336292,0.0021223,0.7028779,0.001049807,0.0004138494,0.00007270202,0.001707345,0.02703764,0.2044128,0.001350612,0.0001601815,0.0574586],"study_design_scores_gemma":[0.01112124,0.0006878226,0.4539142,0.0009346055,0.0006134649,0.00005552706,0.0001560738,0.2375439,0.2845445,0.01010153,0.0001646379,0.0001624655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987529,0.001499823,0.009754251,0.0001058373,0.00003512783,0.0003347765,0.00002144466,0.0000325849,0.0006871904],"genre_scores_gemma":[0.9949298,0.001350671,0.003467524,0.00004432516,0.0000287503,0.00003251904,0.0000304473,0.000008297055,0.0001076503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2489637,"threshold_uncertainty_score":0.3369582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105345349857376,"score_gpt":0.2943692381374073,"score_spread":0.2833157846388335,"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."}}