{"id":"W4413270322","doi":"10.1002/pros.70034","title":"Machine Learning Approach Identifies miRNA Biomarkers for Post Surgical Patient Stratification in Prostate Cancer","year":2025,"lang":"en","type":"article","venue":"The Prostate","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre","funders":"Sunnybrook Foundation","keywords":"Prostate cancer; Medicine; Metastasis; microRNA; Oncology; Receiver operating characteristic; Prostatectomy; Internal medicine; Cancer; Linear discriminant analysis; Bioinformatics; Artificial intelligence; Biology; Computer science","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":[0.0002529116,0.0001128231,0.00008875605,0.00005176211,0.0001172108,0.00004678555,0.0001092838,0.00004709143,0.000004887119],"category_scores_gemma":[0.00004714473,0.0000859913,0.00005560655,0.000136583,0.00007288383,0.000006070929,0.00006001753,0.00006866494,0.000001173232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003154842,"about_ca_system_score_gemma":0.00008771991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001324931,"about_ca_topic_score_gemma":0.00009709417,"domain_scores_codex":[0.9991438,0.00009941091,0.0002253699,0.0002705701,0.00007668987,0.0001841957],"domain_scores_gemma":[0.9995651,0.00001676195,0.00009837876,0.0001949162,0.0001002002,0.00002466678],"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":[0.00207442,0.0001977182,0.01174294,0.0003021713,0.0001961843,0.000002341546,0.0009832574,0.006785249,0.9477032,0.0003855217,0.001007942,0.02861908],"study_design_scores_gemma":[0.005862036,0.0005223845,0.05617198,0.0002627641,0.0001941487,0.00001845082,0.001418403,0.04526138,0.8075057,0.003040179,0.07876496,0.0009776073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941784,0.003027099,0.0002608421,0.0007915094,0.00008668552,0.001200303,0.0001123328,0.00001916178,0.0003236978],"genre_scores_gemma":[0.9969826,0.0002627895,0.0001561501,0.00004836246,0.00002131783,0.0004333478,0.0008518642,0.00001408332,0.001229443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1401975,"threshold_uncertainty_score":0.3506623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007556482189780018,"score_gpt":0.2601650482374067,"score_spread":0.2526085660476267,"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."}}