{"id":"W4280590893","doi":"10.1002/cpz1.442","title":"ntEdit+Sealer: Efficient Targeted Error Resolution and Automated Finishing of Long‐Read Genome Assemblies","year":2022,"lang":"en","type":"article","venue":"Current Protocols","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Human Genome Research Institute; National Institutes of Health; Genome British Columbia; Genome Canada","keywords":"Genome; Bloom filter; Computer science; Sequence assembly; Protocol (science); Pipeline (software); Reference genome; Hybrid genome assembly; Computational biology; Biology; Algorithm; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005065679,0.003265616,0.003078601,0.003011156,0.002513225,0.002918776,0.003554532,0.002327128,0.04048106],"category_scores_gemma":[0.01374376,0.00375265,0.002207079,0.002253503,0.001243415,0.002664685,0.003511268,0.006927496,0.07452828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206026,"about_ca_system_score_gemma":0.003076936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002116857,"about_ca_topic_score_gemma":0.003589737,"domain_scores_codex":[0.9947094,0.0009446588,0.0009213301,0.001363613,0.001528105,0.0005328905],"domain_scores_gemma":[0.9956508,0.001300837,0.0004523117,0.0009777484,0.00132954,0.0002886728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001703283,0.0002331713,0.001761225,0.004604349,0.0001764323,0.0009686275,0.0009416136,0.002374549,0.6286288,0.004488295,0.25101,0.1031097],"study_design_scores_gemma":[0.000217863,0.0003419103,0.002191719,0.0004576851,0.0001107599,0.0009643858,0.0001453465,0.008905138,0.6113036,0.002548622,0.3724501,0.0003627791],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02455252,0.004921998,0.7667417,0.001519523,0.002533512,0.007602598,0.07932456,0.09492714,0.01787646],"genre_scores_gemma":[0.03821367,0.003963447,0.7015714,0.00172534,0.000297783,0.01153912,0.1800689,0.02335549,0.03926484],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04048106,"threshold_uncertainty_score":0.1354226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03622646496452005,"score_gpt":0.3272982239662992,"score_spread":0.2910717590017792,"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."}}