{"id":"W4414585727","doi":"10.1158/1538-7445.pancreatic25-b086","title":"Abstract B086: External validation of a multimodal machine learning system to predict outcomes in advanced pancreatic cancer in the PASS-01 trial","year":2025,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; Université de Montréal; University of British Columbia; University Health Network","funders":"","keywords":"Percentile; Receiver operating characteristic; Cohort; Pancreatic cancer; Hazard ratio; Generalizability theory; Compass; Clinical trial","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":[0.02266553,0.001419323,0.001276813,0.0005097727,0.0003192654,0.001408915,0.001399923,0.001392765,0.004194754],"category_scores_gemma":[0.01624515,0.0003617466,0.001626948,0.0004180046,0.000767567,0.0007354467,0.001304147,0.00202486,0.002947216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007771346,"about_ca_system_score_gemma":0.001532752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002060351,"about_ca_topic_score_gemma":0.001933506,"domain_scores_codex":[0.9954423,0.003332988,0.0001545494,0.0005206817,0.000389229,0.0001602931],"domain_scores_gemma":[0.9937873,0.003588484,0.0005029863,0.000951687,0.0007071117,0.0004624143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.06514465,0.004559979,0.2256528,0.001613046,0.007397868,0.0009717348,0.0005469361,0.3932242,0.01611022,0.002625946,0.0786435,0.2035091],"study_design_scores_gemma":[0.004913797,0.01394616,0.05377964,0.0003220158,0.001994539,0.0006803968,0.0001357046,0.8854542,0.0158461,0.004359848,0.01840745,0.0001601744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9407054,0.001784626,0.02946576,0.001682159,0.0003471909,0.001011585,0.0151642,0.002923784,0.006915286],"genre_scores_gemma":[0.9506454,0.000290966,0.0155296,0.0010223,0.0001739428,0.001112432,0.02709268,0.0003334542,0.003799192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02266553,"threshold_uncertainty_score":0.1198682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03635725401411739,"score_gpt":0.4335930376683845,"score_spread":0.3972357836542671,"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."}}