{"id":"W2513453485","doi":"10.1186/s13059-016-1047-4","title":"Erratum to: A survey of best practices for RNA-seq data analysis","year":2016,"lang":"en","type":"erratum","venue":"Genome biology","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":170,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Biology; Human genetics; Computational biology; Genome Biology; RNA-Seq; Evolutionary biology; Data science; Genetics; Genomics; Computer science; Genome; Gene; Transcriptome","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02208455,0.002033122,0.00176856,0.009991397,0.002283784,0.005240609,0.003201826,0.002814158,0.02942474],"category_scores_gemma":[0.1086459,0.001346321,0.001804797,0.01046853,0.00234629,0.003525533,0.002514477,0.005384057,0.03797437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003383513,"about_ca_system_score_gemma":0.007020696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007195252,"about_ca_topic_score_gemma":0.01190381,"domain_scores_codex":[0.9781425,0.004137862,0.004802509,0.002048951,0.0104522,0.0004158772],"domain_scores_gemma":[0.8941691,0.04456128,0.007292303,0.00729149,0.04512506,0.001560803],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005869577,0.00002077255,0.0003890879,0.002644727,0.00004067145,0.0001893056,0.0001310714,0.0002172615,0.001388292,0.001836929,0.8892753,0.1038079],"study_design_scores_gemma":[0.000008884685,0.00001750939,0.0005583265,0.001257713,0.00003133102,0.0003984983,0.00007406096,0.0002009039,0.001166223,0.001441316,0.9948028,0.00004245709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.001639939,0.1157318,0.09985369,0.1304874,0.5970093,0.0005301369,0.023605,0.01147253,0.01967023],"genre_scores_gemma":[0.01325216,0.2326206,0.269273,0.1572854,0.1016583,0.001634347,0.06038073,0.02982474,0.1340708],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9779155,"threshold_uncertainty_score":0.1167957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109184621899828,"score_gpt":0.4032655179486693,"score_spread":0.2940808960488412,"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."}}