{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002298367,0.0007106616,0.000782221,0.0009369298,0.0003094672,0.0008686213,0.0004172732,0.0008465411,0.002586151],"category_scores_gemma":[0.0003046676,0.0001848803,0.000255309,0.001244228,0.0004321124,0.0008240592,0.0006243507,0.001187356,0.002748956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004278231,"about_ca_system_score_gemma":0.0008102873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003496017,"about_ca_topic_score_gemma":0.0003977504,"domain_scores_codex":[0.9998561,0.00001852683,0.00002245996,0.00003551034,0.00005260004,0.00001483429],"domain_scores_gemma":[0.999908,0.00002677223,0.00001795648,0.000002984891,0.0000292399,0.00001508213],"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":[0.00009915535,0.0000362931,0.000392667,0.0102712,0.0000690532,0.0006118874,0.0001080758,0.0002662186,0.02400758,0.007384824,0.03240694,0.9243461],"study_design_scores_gemma":[0.000007391402,0.00004873568,0.0007054069,0.0006761522,0.00005623814,0.002423416,0.00004013084,0.00006551657,0.003381163,0.001755805,0.9908242,0.00001575649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003836769,0.9948223,0.0006470906,0.000414933,0.0005347311,0.00000934863,0.00005811496,0.00003633635,0.003093464],"genre_scores_gemma":[0.003625019,0.9927621,0.0006967781,0.0003784558,0.0003508316,0.00001665714,0.0001161905,0.000007810182,0.002046089],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002586151,"threshold_uncertainty_score":0.008651555,"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."}}