{"id":"W2959872456","doi":"10.3389/fgene.2019.00736","title":"Sentieon DNASeq Variant Calling Workflow Demonstrates Strong Computational Performance and Accuracy","year":2019,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":281,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Center for Individualized Medicine, Mayo Clinic; Carl R. Woese Institute for Genomic Biology; Mayo Clinic","keywords":"Computer science; Workflow; Scalability; Pipeline (software); Software; Software deployment; Sample (material); Data mining; Software engineering; Database; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001107639,0.0001523752,0.0001589256,0.00004990521,0.00006319684,0.0000303458,0.0001211889,0.00009954769,0.000005157915],"category_scores_gemma":[0.00001594771,0.000159801,0.00003399535,0.00006836013,0.00007021875,0.000001479633,0.0001088102,0.00008400431,0.000002919638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001337594,"about_ca_system_score_gemma":0.00005478886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003596909,"about_ca_topic_score_gemma":0.000006029204,"domain_scores_codex":[0.9991099,0.00002800025,0.0002054271,0.0003135453,0.00009577836,0.0002473439],"domain_scores_gemma":[0.9996417,0.00001515015,0.0000638363,0.0001736696,0.00005191418,0.00005373196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005788115,0.00003654762,0.8915982,0.00004415686,0.00009147962,0.000002882246,0.0001012213,0.06937812,0.01592986,0.00004279463,0.0009705152,0.02174629],"study_design_scores_gemma":[0.002686595,0.0006093741,0.7375185,0.00007536071,0.00006705172,0.00003962894,0.000776394,0.2175604,0.01816393,0.001491391,0.01998659,0.001024772],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98522,0.005086502,0.008379977,0.00003633671,0.0005507611,0.0002046845,0.00001448875,0.000002741632,0.0005045246],"genre_scores_gemma":[0.9517812,0.002185018,0.04568409,0.00006696652,0.00009619077,0.000007605009,0.00003690018,0.00001728841,0.0001247359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1540798,"threshold_uncertainty_score":0.6516497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007113183464522518,"score_gpt":0.213585716453636,"score_spread":0.2064725329891135,"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."}}