{"id":"W3087252472","doi":"10.3390/genes11091098","title":"Building towards Precision Oncology for Pancreatic Cancer: Real-World Challenges and Opportunities","year":2020,"lang":"en","type":"review","venue":"Genes","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Precision oncology; Profiling (computer programming); Pancreatic cancer; Precision medicine; Pancreatic ductal adenocarcinoma; Clinical Oncology; Biomarker discovery; Medicine; Germline; DNA sequencing; Biomarker; Computational biology; Bioinformatics; Oncology; Internal medicine; Cancer; Biology; Gene; Computer science; Proteomics; Pathology; Genetics","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":[0.002897206,0.0006005121,0.001146845,0.002086808,0.0004108276,0.002330319,0.0009433118,0.002141378,0.003334537],"category_scores_gemma":[0.00325469,0.0002706497,0.0007113578,0.001842113,0.001320259,0.00346422,0.001382735,0.004121322,0.001981323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360868,"about_ca_system_score_gemma":0.002882877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001145195,"about_ca_topic_score_gemma":0.002431947,"domain_scores_codex":[0.9992437,0.0002410577,0.00007322191,0.0001009843,0.0002678642,0.00007310301],"domain_scores_gemma":[0.9969254,0.002027553,0.0001690169,0.00009461851,0.000602294,0.0001810686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005294507,0.0000599388,0.0002933396,0.0135282,0.0000873867,0.000252251,0.0001878832,0.0007794339,0.001720405,0.03023129,0.03464174,0.9181652],"study_design_scores_gemma":[0.000009476711,0.00008574721,0.0003533452,0.004902003,0.00004986888,0.0007437988,0.0001493874,0.0001434405,0.0003963812,0.01223547,0.9809091,0.00002189994],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000154797,0.9928393,0.0007009222,0.004237086,0.0004342146,0.000006290977,0.00002342541,0.00002269187,0.001581232],"genre_scores_gemma":[0.001257546,0.9949935,0.0009837002,0.001803903,0.0004450293,0.000009402443,0.0000322192,0.000006170561,0.0004686702],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003334537,"threshold_uncertainty_score":0.01532203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3745743232346988,"score_gpt":0.4934109164994511,"score_spread":0.1188365932647523,"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."}}