{"id":"W4291624850","doi":"10.11152/mu-3503","title":"Quantitative contrast-enhanced endoscopic ultrasound in pancreatic ductal adenocarcinoma and pancreatic neuroendocrine tumors: can we predict survival using perfusion parameters? A pilot study.","year":2022,"lang":"en","type":"article","venue":"Medical Ultrasonography","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cytodiagnostics (Canada)","funders":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii","keywords":"Medicine; Pancreatic ductal adenocarcinoma; Endoscopic ultrasound; Contrast-enhanced ultrasound; Internal medicine; Proportional hazards model; Perfusion; Pancreatic cancer; Radiology; Vascularity; Oncology; Neuroendocrine tumors; Survival analysis; Stage (stratigraphy); Adenocarcinoma; Area under the curve; Gastroenterology; Ultrasound; Cancer","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001359676,0.0005340929,0.001739778,0.0008483768,0.0005132335,0.00005231438,0.0003656429,0.00006818146,0.001032222],"category_scores_gemma":[0.002995711,0.0004720019,0.0001606788,0.001526529,0.000920149,0.0001221475,0.000229062,0.001568336,0.000004594446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002456818,"about_ca_system_score_gemma":0.0007160411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003277696,"about_ca_topic_score_gemma":0.0006398376,"domain_scores_codex":[0.9930812,0.00176245,0.001043764,0.001030314,0.001934728,0.00114751],"domain_scores_gemma":[0.9942173,0.004054294,0.0002337484,0.0005241737,0.0001037709,0.0008667558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002404409,0.002994919,0.9790413,0.0002020537,0.0003758322,0.002501121,0.002762194,0.00001154166,0.009344988,0.0000640763,0.00003796006,0.0002595949],"study_design_scores_gemma":[0.01263022,0.02506588,0.9369864,0.0004744881,0.0008002057,0.001763034,0.01852591,0.00296708,0.0001820294,0.0001825093,0.00001932161,0.0004028713],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931952,0.002231332,0.0002538491,0.0008815326,0.0002609724,0.002756594,0.00007923924,0.0001079139,0.0002333781],"genre_scores_gemma":[0.9965466,0.001102706,0.001123925,0.0003081314,0.0001032094,0.0006099016,0.00007552785,0.00006809179,0.00006185666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04205485,"threshold_uncertainty_score":0.999881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04729661254704993,"score_gpt":0.3245984778428677,"score_spread":0.2773018652958178,"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."}}