{"id":"W3206666009","doi":"10.46471/gigabyte.31","title":"Atria: an ultra-fast and accurate trimmer for adapter and quality trimming","year":2021,"lang":"en","type":"article","venue":"Gigabyte","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; Canadian Food Inspection Agency","funders":"Canadian Food Inspection Agency","keywords":"Trimming; Adapter (computing); Computer science; Byte; Algorithm; Matching (statistics); Parallel computing; Computer hardware; Operating system; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000183418,0.0001177625,0.0001604404,0.00001168596,0.0001116222,0.00003611494,0.00004946215,0.00008272332,0.000003316073],"category_scores_gemma":[0.00006408944,0.0001116173,0.00004996988,0.00002667052,0.00005471649,0.000001386445,0.00004731667,0.00003646297,5.458997e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002693823,"about_ca_system_score_gemma":0.00003632404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001725903,"about_ca_topic_score_gemma":0.0000630575,"domain_scores_codex":[0.9992355,0.00004324449,0.000163864,0.0003441349,0.00004151793,0.0001717518],"domain_scores_gemma":[0.9995835,0.00002813502,0.00004939814,0.0001927897,0.00007511509,0.00007108163],"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":[0.0001030104,0.00001950065,0.003410834,0.00002582234,0.0000769555,0.000001118055,0.0001545267,0.000004472045,0.9836251,0.0001907595,0.0001397103,0.01224826],"study_design_scores_gemma":[0.002831275,0.0004480322,0.07244757,0.00001198043,0.00009834526,0.00003393149,0.00102262,0.00004225644,0.8286304,0.0004934522,0.09345667,0.0004834671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919317,0.006276411,0.0008485439,0.0002223508,0.0001119471,0.0001340698,0.00007264467,0.000002506872,0.0003998046],"genre_scores_gemma":[0.9962389,0.001133856,0.001450898,0.0003011927,0.000215513,0.00001733401,0.00004970755,0.00001490328,0.0005776385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1549946,"threshold_uncertainty_score":0.4551621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04349607245292741,"score_gpt":0.3048034750527828,"score_spread":0.2613074025998554,"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."}}