{"id":"W3091991241","doi":"10.3389/frai.2020.550890","title":"Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma","year":2020,"lang":"en","type":"article","venue":"Frontiers in Artificial Intelligence","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Sinai Health System; Sunnybrook Health Science Centre; Health Sciences Centre; Lunenfeld-Tanenbaum Research Institute; University of Alberta; University Health Network; University of Toronto","funders":"Canadian Cancer Society Research Institute; Terry Fox Research Institute; Pancreatic Cancer Canada Foundation; Hebrew University of Jerusalem; Government of Ontario; Ontario Institute for Cancer Research; Princess Margaret Cancer Foundation","keywords":"Pancreatic ductal adenocarcinoma; Value (mathematics); Medicine; Pancreatic carcinoma; Internal medicine; Oncology; Pancreatic cancer; Computer science; Cancer; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004722338,0.0001745509,0.0005110829,0.000270864,0.00004349585,0.00002150025,0.0001822367,0.0001088704,0.00006718047],"category_scores_gemma":[0.002144709,0.0001672086,0.00009599743,0.0007819642,0.0002083532,0.00007189927,0.00002456727,0.00097869,0.000005659018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007002355,"about_ca_system_score_gemma":0.0001567279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002542682,"about_ca_topic_score_gemma":0.00001732253,"domain_scores_codex":[0.9981478,0.000177615,0.0005716776,0.0003863787,0.0003388821,0.000377628],"domain_scores_gemma":[0.9994068,0.0001634404,0.00005504889,0.0001480107,0.00004925299,0.0001774841],"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":[0.0008923824,0.0001765479,0.9244406,0.000393537,0.00003597315,0.0003753664,0.003588503,0.04797846,0.006478031,0.001045805,0.0002708506,0.01432394],"study_design_scores_gemma":[0.0003751408,0.0006627159,0.09432697,0.0006669737,0.0000893544,0.00002072561,0.00225222,0.8790003,0.02049135,0.00157757,0.0002614094,0.0002752564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8435221,0.001590071,0.15016,0.003405192,0.0002834484,0.0004754672,0.000002312708,0.00004604687,0.0005153769],"genre_scores_gemma":[0.9863195,0.00006353453,0.01296826,0.0004261795,0.0001226818,0.00001933416,0.00001565571,0.00002990028,0.00003488673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8310218,"threshold_uncertainty_score":0.6818568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112175603968496,"score_gpt":0.2777843000506922,"score_spread":0.2566625440110072,"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."}}