{"id":"W4223916144","doi":"10.7717/peerj.13300","title":"PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification","year":2022,"lang":"en","type":"article","venue":"PeerJ","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Vale Canada Limited","keywords":"Genome; Identification (biology); Pipeline (software); Computational biology; Annotation; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Biology; Coronavirus; Computer science; Data science; Virus; Genetics; Gene; Infectious disease (medical specialty); Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00350861,0.0033907,0.001650144,0.003420652,0.001601931,0.002605292,0.002838206,0.001483994,0.03695397],"category_scores_gemma":[0.01264272,0.001941561,0.002062702,0.002384172,0.000634295,0.003053124,0.003654483,0.002361961,0.05085705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002544,"about_ca_system_score_gemma":0.004172522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006139095,"about_ca_topic_score_gemma":0.005873644,"domain_scores_codex":[0.9978941,0.0002431316,0.0002010445,0.0008051582,0.0006680024,0.0001885848],"domain_scores_gemma":[0.9964352,0.001072714,0.0003076063,0.000843621,0.001030572,0.0003102248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002326027,0.0001651183,0.007667171,0.003634446,0.0006514978,0.0009137039,0.0009294905,0.003515085,0.05917887,0.002931453,0.7784685,0.1396185],"study_design_scores_gemma":[0.000619835,0.0004295263,0.01127667,0.0004624888,0.0003233845,0.001377839,0.0003106567,0.03815744,0.0836553,0.009713051,0.853146,0.0005278898],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.008497557,0.001434457,0.1798937,0.0006840941,0.0006050231,0.0008418043,0.173258,0.626185,0.008600372],"genre_scores_gemma":[0.0369722,0.001223274,0.2021492,0.0007198212,0.0002219434,0.001568634,0.6378441,0.1092223,0.01007859],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03695397,"threshold_uncertainty_score":0.1236234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06067697167216344,"score_gpt":0.3689058206208236,"score_spread":0.3082288489486602,"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."}}