{"id":"W2810425915","doi":"10.1093/bioinformatics/bty544","title":"lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Nanopore sequencing; Computer science; Reference genome; Genomics; DNA sequencing; Throughput; Genome; Data mining; Computational biology; Biology; Wireless; Genetics; Gene; Telecommunications","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":[0.005356895,0.003278341,0.002270765,0.002528476,0.002291294,0.002353368,0.004849297,0.002658474,0.02576203],"category_scores_gemma":[0.01524133,0.002186226,0.002488951,0.003050316,0.0009019248,0.003568676,0.00319709,0.00381106,0.02357649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102606,"about_ca_system_score_gemma":0.003107386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002597118,"about_ca_topic_score_gemma":0.005613445,"domain_scores_codex":[0.9960876,0.0009255192,0.0004871872,0.001125696,0.001043138,0.0003308548],"domain_scores_gemma":[0.996788,0.001752826,0.000375799,0.000380719,0.000474737,0.0002279312],"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":[0.006143794,0.0003801736,0.006554245,0.008176181,0.001541724,0.002529674,0.001228153,0.01774419,0.1478074,0.01034698,0.5458435,0.2517039],"study_design_scores_gemma":[0.002446001,0.001175942,0.01044664,0.001215412,0.0005132739,0.004602267,0.0007660409,0.3616696,0.193396,0.0403044,0.3823545,0.00111],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01942495,0.002890513,0.5374782,0.0008618138,0.001113441,0.0008039944,0.06158083,0.3718878,0.003958532],"genre_scores_gemma":[0.04460206,0.0006708212,0.8179567,0.0009097562,0.0001256833,0.001319937,0.1021012,0.0276897,0.004624104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02576203,"threshold_uncertainty_score":0.08618253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0409620581989204,"score_gpt":0.2835077408358809,"score_spread":0.2425456826369605,"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."}}