{"id":"W2598764473","doi":"10.1002/cbin.10770","title":"MicroRNA: an important regulator in acute myeloid leukemia","year":2017,"lang":"en","type":"review","venue":"Cell Biology International","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Institute for Biodiagnostics","funders":"","keywords":"microRNA; Myeloid leukemia; Biology; Haematopoiesis; Carcinogenesis; Regulator; Cancer research; Leukemia; Epigenetics; Myeloid; Bioinformatics; Computational biology; Immunology; Gene; Stem cell; 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"],"consensus_categories":[],"category_scores_codex":[0.0002874137,0.000447063,0.0007351236,0.0002228681,0.00007505556,0.00005493094,0.001212292,0.0009752701,0.0001281986],"category_scores_gemma":[0.00006282958,0.0004101664,0.0003982535,0.00004829648,0.0001967522,0.0000102393,0.0003325136,0.0002795474,0.00006906197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002605433,"about_ca_system_score_gemma":0.0007303993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002195586,"about_ca_topic_score_gemma":0.00004146222,"domain_scores_codex":[0.997762,0.0001536512,0.0007691234,0.0008759768,0.000105144,0.0003341514],"domain_scores_gemma":[0.9980156,0.00001479939,0.0008180306,0.0009293057,0.0001014948,0.0001207305],"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":[0.0001969613,0.0003923698,0.001626638,0.001788999,0.001785481,0.0002014811,0.0000365787,0.000009573674,0.1601358,0.0005272706,0.006707053,0.8265918],"study_design_scores_gemma":[0.0003712982,0.00007408042,0.0001777787,0.0003870733,0.0001569353,0.00008168713,0.000002118244,0.00001647602,0.00212751,0.00007278113,0.9961079,0.000424306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.008981737,0.9870305,0.00003077972,0.00002131549,0.001259044,0.000468771,0.00055654,0.00001765816,0.001633622],"genre_scores_gemma":[0.001615148,0.9830272,0.0003188894,0.00005407914,0.0008383689,0.0001011921,0.01207678,0.00006526139,0.001903126],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9894009,"threshold_uncertainty_score":0.999835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0276266599921494,"score_gpt":0.3364402563019659,"score_spread":0.3088135963098165,"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."}}