{"id":"W2611221674","doi":"10.6000/1927-7229.2017.06.02.4","title":"In silico Meta-Analysis of Circulatory microRNAs in Prostate Cancer","year":2017,"lang":"en","type":"article","venue":"Journal of Analytical Oncology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"microRNA; Biology; Computational biology; In silico; Carcinogenesis; Wnt signaling pathway; Prostate cancer; Bioinformatics; Cancer; Signal transduction; Gene; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007259112,0.0001090724,0.0009019588,0.0003692177,0.00002359853,0.00001234758,0.0003006727,0.0001552347,0.0001766611],"category_scores_gemma":[0.0002791236,0.00008884457,0.0007378926,0.0001788536,0.0001830832,0.00001350297,0.00007898564,0.0001605342,0.000001019578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001142042,"about_ca_system_score_gemma":0.0003639327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000112016,"about_ca_topic_score_gemma":0.0008655482,"domain_scores_codex":[0.9986048,0.0001432382,0.0007435274,0.0001794524,0.0001520644,0.0001769725],"domain_scores_gemma":[0.9984694,0.00003593575,0.0008452734,0.0003449218,0.0002122719,0.00009225962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007742787,0.0007865261,0.1655201,0.00004397778,0.05442113,0.0002582175,0.0001328306,0.009324058,0.7666191,0.0002558572,0.001172657,0.0006912992],"study_design_scores_gemma":[0.002590904,0.0006372316,0.8643843,0.00001647099,0.06613503,0.00005175454,0.00007346514,0.002214682,0.048918,0.0004199093,0.01425343,0.0003048546],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955378,0.002344115,0.00003175272,0.001577307,0.00007365294,0.0000778765,0.00001512005,4.512702e-7,0.0003419302],"genre_scores_gemma":[0.9992193,0.0001987301,0.0001607784,0.0001850866,0.00006973746,0.000003700931,0.000003880538,0.000007823226,0.0001509623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7177011,"threshold_uncertainty_score":0.3622977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04743074863371256,"score_gpt":0.3763389043678759,"score_spread":0.3289081557341634,"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."}}