{"id":"W4293799471","doi":"10.1016/j.ygeno.2022.110474","title":"Epigenome-wide DNA methylation and transcriptome profiling of localized and locally advanced prostate cancer: Uncovering new molecular markers","year":2022,"lang":"en","type":"article","venue":"Genomics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"CancerCare Manitoba; Public Health Ontario; University of Toronto; University of Manitoba","funders":"CancerCare Manitoba Foundation; Manitoba Medical Service Foundation","keywords":"Epigenome; Biology; DNA methylation; Transcriptome; Prostate cancer; Computational biology; Gene expression profiling; Genetics; Profiling (computer programming); Epigenomics; Epigenetics; Methylation; DNA; Cancer; Gene; Gene expression","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":[0.0002681129,0.0001381866,0.0001730472,0.00005467472,0.0001007955,0.00001548537,0.00008196967,0.00005667324,0.000008022887],"category_scores_gemma":[0.00002726198,0.0001617603,0.00004500958,0.00009373468,0.00004784171,0.000005642793,0.0001157916,0.0000813393,1.126164e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004330352,"about_ca_system_score_gemma":0.0001639397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007762104,"about_ca_topic_score_gemma":0.00002637045,"domain_scores_codex":[0.9990359,0.00006832865,0.0002690881,0.0003236826,0.0001188006,0.0001842044],"domain_scores_gemma":[0.9995529,0.00001417641,0.0001350755,0.0001674683,0.00004343463,0.00008696738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003014674,0.00001070187,0.006237553,0.00004676004,0.00004786198,0.000001327945,0.0002206254,0.02708679,0.9430835,0.00004059603,0.00000310324,0.02291971],"study_design_scores_gemma":[0.001531333,0.0004179953,0.002727986,0.00001037664,0.00004919415,0.000001191136,0.0002880728,0.001078663,0.977187,0.001057401,0.01537412,0.0002766138],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9657782,0.01871682,0.01476193,0.0001034908,0.0000952202,0.0003970465,0.00005014979,0.000007042471,0.00009012768],"genre_scores_gemma":[0.9882536,0.003956008,0.00740787,0.00008963317,0.00002655945,0.0000370552,0.00009609397,0.00003217205,0.0001010077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03410355,"threshold_uncertainty_score":0.6596394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006397976646941258,"score_gpt":0.2316444938868587,"score_spread":0.2252465172399175,"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."}}