{"id":"W2953326935","doi":"10.1093/bioinformatics/btz400","title":"ntEdit: scalable genome sequence polishing","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia; Genome British Columbia; Université Laval; Natural Resources Canada; Ministry of Forests","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Sequence (biology); Scalability; Polishing; Computer science; Whole genome sequencing; Genome; Computational biology; Genetics; Biology; Gene; Materials science; Database; Metallurgy","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":[0.002397788,0.002464843,0.001499029,0.001349361,0.001149038,0.001792068,0.003168288,0.001154647,0.01099362],"category_scores_gemma":[0.008804723,0.001358049,0.002145539,0.001784814,0.0007824562,0.002222088,0.002439484,0.003280113,0.01140517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009542556,"about_ca_system_score_gemma":0.001539205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003515517,"about_ca_topic_score_gemma":0.004666283,"domain_scores_codex":[0.9982918,0.0002632597,0.0001740847,0.0005936857,0.0005394948,0.0001377034],"domain_scores_gemma":[0.9971175,0.001065256,0.0002572508,0.0008004605,0.0005629479,0.0001966297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004426415,0.0004285576,0.006770637,0.003443937,0.0007699016,0.001333883,0.001131794,0.04643041,0.2481995,0.006317002,0.329496,0.351252],"study_design_scores_gemma":[0.001467267,0.0006537031,0.005126001,0.0002358246,0.000246319,0.001212944,0.0003063081,0.4158997,0.3817342,0.01647806,0.176154,0.000485787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.0308434,0.001085537,0.390952,0.0005593137,0.0005720819,0.0007035224,0.02718834,0.5437394,0.004356453],"genre_scores_gemma":[0.08277246,0.0006713597,0.7792966,0.0006929279,0.0001097648,0.001336024,0.08930602,0.04038668,0.005428135],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.01099362,"threshold_uncertainty_score":0.03677738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446762705254454,"score_gpt":0.2310440146055117,"score_spread":0.2165763875529672,"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."}}