{"id":"W3002269417","doi":"10.1101/2020.01.27.921817","title":"HASLR: Fast Hybrid Assembly of Long Reads","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanopore sequencing; Computer science; Sequence assembly; Genome; DNA sequencing; Third generation; Contiguity; Range (aeronautics); Computational biology; Biology; Engineering; Operating system; Genetics; DNA","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":[0.004648488,0.002410831,0.001995718,0.001926535,0.00128242,0.002460123,0.00273177,0.001706185,0.01996909],"category_scores_gemma":[0.006012358,0.0019681,0.002390388,0.001501206,0.0006630177,0.001623751,0.003012494,0.003294453,0.01950374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006295897,"about_ca_system_score_gemma":0.00104032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001178926,"about_ca_topic_score_gemma":0.001542425,"domain_scores_codex":[0.9965161,0.001067562,0.0003625343,0.0007991831,0.001017408,0.0002371668],"domain_scores_gemma":[0.9961627,0.001778089,0.0002801966,0.0009148073,0.0006585692,0.0002055895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003624775,0.0003839462,0.002467888,0.004611713,0.001625935,0.00125146,0.001037906,0.03162441,0.3831089,0.01550099,0.2282616,0.3265006],"study_design_scores_gemma":[0.0005934725,0.0007857317,0.003078719,0.0003749821,0.0002183891,0.001278612,0.0002133682,0.3082104,0.4462238,0.01685722,0.2214766,0.0006886693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01328765,0.0008922152,0.7759242,0.0002356171,0.0005063923,0.0004720408,0.01147199,0.1945396,0.002670185],"genre_scores_gemma":[0.04866332,0.0003060997,0.8840408,0.0002576411,0.0001129814,0.001121918,0.03975935,0.02009816,0.00563969],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01996909,"threshold_uncertainty_score":0.06680334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433931494838721,"score_gpt":0.2195771886657668,"score_spread":0.2052378737173796,"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."}}