{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009203963,0.001171199,0.001549932,0.001435042,0.001803227,0.003023812,0.002294,0.001785967,0.009149823],"category_scores_gemma":[0.01867686,0.0008208308,0.001680483,0.001708555,0.001522359,0.001643614,0.002195951,0.002441546,0.0093858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001116795,"about_ca_system_score_gemma":0.003043503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007934893,"about_ca_topic_score_gemma":0.01790137,"domain_scores_codex":[0.9946676,0.0008830444,0.0004642064,0.001517512,0.002186341,0.0002812305],"domain_scores_gemma":[0.9924569,0.003069395,0.0003152316,0.001766345,0.002100243,0.0002919475],"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":[0.002800375,0.0004537147,0.02467733,0.002479015,0.0008452327,0.000844268,0.001798233,0.02133526,0.5153734,0.02570926,0.1014843,0.3021996],"study_design_scores_gemma":[0.0005431729,0.0009163938,0.0245537,0.0004823485,0.0003970097,0.00284966,0.0004585125,0.1632037,0.4680282,0.03705864,0.3002775,0.001231261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1312489,0.001911102,0.703087,0.00202862,0.00104853,0.001010792,0.03319994,0.09953038,0.02693474],"genre_scores_gemma":[0.133246,0.0004872178,0.8178635,0.001026945,0.0000748278,0.0007896509,0.02775148,0.0113047,0.007455684],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009203963,"threshold_uncertainty_score":0.04867578,"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."}}