{"id":"W4411679478","doi":"10.1016/j.jvsv.2025.102283","title":"Predictors of inferior vena cava filter retrieval in a population-based Canadian cohort","year":2025,"lang":"en","type":"article","venue":"Journal of Vascular Surgery Venous and Lymphatic Disorders","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"North Pacific Marine Science Organization; Institute for Clinical Evaluative Sciences; University of Toronto; Toronto General Hospital; Toronto East General Hospital; St. Michael's Hospital; Queen's University","funders":"Institut canadien d'information sur la santé; Ontario Ministry of Health and Long-Term Care","keywords":"Medicine; Inferior vena cava; Inferior vena cava filter; Cohort; Population; Filter (signal processing); Internal medicine; Environmental health; Computer vision; Thrombosis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009133983,0.0001397794,0.0008365117,0.0009200887,0.00005567699,0.00001950899,0.00006832908,0.00008084467,0.00006031418],"category_scores_gemma":[0.0003467748,0.0001225736,0.0002832267,0.0004205731,0.00004801181,0.00007592429,0.00001394933,0.00007842985,5.753622e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002319305,"about_ca_system_score_gemma":0.001128533,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03170023,"about_ca_topic_score_gemma":0.01183797,"domain_scores_codex":[0.998504,0.00007700069,0.0007057331,0.0001389331,0.0003263746,0.0002479223],"domain_scores_gemma":[0.9991014,0.0001842828,0.0002447776,0.0001912113,0.0001098409,0.0001684816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007172688,0.0006190189,0.9918981,0.0003470988,0.0005831564,0.00004990907,0.0001905419,0.0004129994,0.00001027816,0.00005687977,0.0007296849,0.005030646],"study_design_scores_gemma":[0.001148873,0.000182907,0.9935342,0.0008060099,0.0004727001,0.000006898157,0.0001378572,0.0002998809,0.00002016183,0.000109737,0.003182903,0.0000978684],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954877,0.002467334,0.0000775912,0.0008134459,0.0003955705,0.0003547717,0.00000439665,0.000004979981,0.0003941863],"genre_scores_gemma":[0.9980087,0.001362601,0.00005565709,0.0004854237,0.00003223452,0.000005213547,0.00001402319,0.00001443838,0.00002176943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01986226,"threshold_uncertainty_score":0.9747478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005991753436276554,"score_gpt":0.2281158886287423,"score_spread":0.2221241351924658,"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."}}