{"id":"W4385442241","doi":"10.1158/1078-0432.ccr-23-0887","title":"hENT1 as a Predictive Biomarker in PDAC—Response","year":2023,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Biomarker; Medicine; Oncology; FOLFIRINOX; Population; Biomarker discovery; Internal medicine; Computational biology; Bioinformatics; Biology; Cancer; Gene; Genetics; Colorectal cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007287297,0.0004295149,0.001038742,0.0007138984,0.0004220989,0.00204337,0.0008734642,0.001190627,0.003559849],"category_scores_gemma":[0.01082762,0.0002037226,0.000847091,0.0008188796,0.0005597526,0.001168797,0.0005194635,0.003424373,0.001519644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001785243,"about_ca_system_score_gemma":0.0007129986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001004939,"about_ca_topic_score_gemma":0.001751042,"domain_scores_codex":[0.9978507,0.0007847452,0.0001967578,0.0004061337,0.0006109331,0.0001508135],"domain_scores_gemma":[0.9929155,0.003313468,0.0006401231,0.0005170123,0.001838728,0.0007752493],"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":[0.02574681,0.000463169,0.1971991,0.001984802,0.001117931,0.002122089,0.0005855557,0.004756639,0.03808203,0.003351489,0.2555859,0.4690046],"study_design_scores_gemma":[0.00212804,0.007545795,0.3169042,0.00149585,0.002106843,0.01041214,0.001368298,0.0322972,0.1136262,0.02166361,0.4899259,0.0005260818],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4351837,0.1494475,0.02740858,0.3069192,0.02512208,0.001025295,0.01006382,0.001665354,0.04316442],"genre_scores_gemma":[0.9131238,0.01178195,0.01452259,0.03496117,0.009948077,0.000490597,0.004352065,0.0003915657,0.01042821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007287297,"threshold_uncertainty_score":0.03853935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4565912749497369,"score_gpt":0.650337593659994,"score_spread":0.1937463187102571,"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."}}