{"id":"W3109964992","doi":"10.3389/fgene.2020.612515","title":"A Distributed Whole Genome Sequencing Benchmark Study","year":2020,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; McGill University; McGill Genome Centre; Ontario Genomics; Canada's Michael Smith Genome Sciences Centre; SickKids Foundation; University of Toronto; Provincial Health Services Authority","funders":"Hospital for Sick Children; Canada Foundation for Innovation; Genome British Columbia; Canadian Institutes of Health Research; Ontario Genomics; Genome Canada; University of Toronto; GlaxoSmithKline","keywords":"Genome; Benchmark (surveying); Computational biology; Whole genome sequencing; Computer science; DNA sequencing; Biology; Genetics; Gene; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01376474,0.0008633104,0.001209723,0.001423041,0.001590847,0.001998339,0.002080532,0.00187242,0.001309815],"category_scores_gemma":[0.02466975,0.000329046,0.001294017,0.003275553,0.00109983,0.001343739,0.001963678,0.001748101,0.0004274203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002477094,"about_ca_system_score_gemma":0.001868376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100187,"about_ca_topic_score_gemma":0.008377699,"domain_scores_codex":[0.9885356,0.004874692,0.0006043409,0.003388366,0.002129394,0.0004676947],"domain_scores_gemma":[0.9704638,0.01094404,0.001732028,0.009247238,0.006141655,0.001471242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.009140024,0.009431113,0.3657004,0.001585325,0.004086699,0.00321527,0.002919617,0.2534965,0.114859,0.02347769,0.02866999,0.1834184],"study_design_scores_gemma":[0.002069905,0.009997949,0.4630856,0.0002695874,0.001477648,0.004946459,0.003222706,0.3429916,0.07978433,0.03947835,0.05221405,0.0004618666],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.925761,0.0007062508,0.0609469,0.0005645304,0.0001432663,0.0007089257,0.006839703,0.0007620386,0.003567297],"genre_scores_gemma":[0.9158999,0.0002165621,0.05471688,0.0004375151,0.0001047657,0.000886588,0.02610686,0.0003303997,0.001300521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01376474,"threshold_uncertainty_score":0.07279575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01141862227032207,"score_gpt":0.2202589005690563,"score_spread":0.2088402782987343,"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."}}