{"id":"W2039403882","doi":"10.21037/cco.2016.03.09","title":"MicroRNAs in nasopharyngeal carcinoma","year":2016,"lang":"en","type":"review","venue":"Chinese Clinical Oncology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre","funders":"","keywords":"microRNA; Nasopharyngeal carcinoma; Disease; Radioresistance; Carcinogenesis; Medicine; Cancer; Bioinformatics; Computational biology; Cancer research; Biology; Radiation therapy; Pathology; Internal medicine; Gene; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0008995893,0.0005295445,0.002254886,0.0001512642,0.00003449389,0.00001126978,0.0006242059,0.001922672,0.0001460965],"category_scores_gemma":[0.00113202,0.000353987,0.001094389,0.000200688,0.0002893137,0.000003726217,0.0004475069,0.0005079852,0.0004184144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001773422,"about_ca_system_score_gemma":0.001515474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000587694,"about_ca_topic_score_gemma":0.00004085476,"domain_scores_codex":[0.9957589,0.0009572146,0.001743209,0.00100942,0.00009597461,0.000435272],"domain_scores_gemma":[0.9977328,0.0004348393,0.0007047128,0.0008453425,0.00007763104,0.0002046632],"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":[0.00009011024,0.0003509895,0.001855353,0.001456267,0.0001552618,0.00009172715,0.000003213665,1.336901e-7,0.0002253915,0.00001304191,0.005682269,0.9900762],"study_design_scores_gemma":[0.001292617,0.000387255,0.00284136,0.00104349,0.0001400023,0.00007820009,6.137051e-7,5.767761e-7,0.000009312028,0.00006980953,0.9937422,0.0003945972],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00862006,0.9875045,0.00001606065,0.0000847781,0.00145841,0.0007185355,0.00009031517,0.00001659423,0.001490773],"genre_scores_gemma":[0.001944319,0.9937672,0.0001292299,0.0001826263,0.002029462,0.0001258416,0.0007159618,0.00009226587,0.001013116],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9896817,"threshold_uncertainty_score":0.9998912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06230377510801446,"score_gpt":0.4368324113977353,"score_spread":0.3745286362897209,"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."}}