{"id":"W4312141111","doi":"10.3390/cancers14246224","title":"CT Radiomics and Whole Genome Sequencing in Patients with Pancreatic Ductal Adenocarcinoma: Predictive Radiogenomics Modeling","year":2022,"lang":"en","type":"article","venue":"Cancers","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Public Health Ontario; University of Toronto; University Health Network","funders":"University of Toronto","keywords":"Radiogenomics; Radiomics; Pancreatic ductal adenocarcinoma; Medicine; Adenocarcinoma; Genome; Computational biology; Pancreatic cancer; Internal medicine; Biology; Radiology; Gene; Cancer; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008418626,0.0003215027,0.0003343532,0.0008250385,0.0001224163,0.0006950771,0.0003252215,0.0002668303,0.0005551759],"category_scores_gemma":[0.002914738,0.0002059179,0.0004914857,0.0005830564,0.0001705428,0.0002847929,0.0003175497,0.0002456675,0.0001811436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002065851,"about_ca_system_score_gemma":0.000250139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001662859,"about_ca_topic_score_gemma":0.001387464,"domain_scores_codex":[0.9997681,0.00009890027,0.00001715904,0.00006406866,0.00003088023,0.00002095671],"domain_scores_gemma":[0.9992104,0.00042963,0.0001717198,0.00007982901,0.00004928997,0.00005909373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003474434,0.00004197329,0.9749326,0.00001366842,0.0001015661,0.0001957434,0.00004857915,0.01094888,0.001548778,0.0001043297,0.00009767229,0.01161876],"study_design_scores_gemma":[0.00002455443,0.0003329994,0.6500278,0.00001807727,0.000240348,0.001347998,0.0001762268,0.3431926,0.002780009,0.0009340869,0.0009033669,0.00002196595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935534,0.0001901593,0.005634139,0.00006207993,0.00000263937,0.000007123288,0.0002943731,0.00003756891,0.0002185347],"genre_scores_gemma":[0.9982749,0.00006869173,0.001250498,0.000007852555,0.000003871772,0.000005298731,0.0003268921,0.000006364211,0.00005558403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001662859,"threshold_uncertainty_score":0.004452229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168064702434963,"score_gpt":0.2562179711362157,"score_spread":0.2345373241118661,"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."}}