{"id":"W2994769036","doi":"10.1016/j.jmoldx.2019.10.011","title":"Sample Tracking Using Unique Sequence Controls","year":2019,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre; Simon Fraser University","funders":"Provincial Health Services Authority; Genome British Columbia","keywords":"Barcode; Sample (material); DNA sequencing; Computational biology; Pipeline (software); Sequence (biology); Genotyping; Massive parallel sequencing; Biology; Computer science; Data mining; Genetics; DNA; Gene; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003182266,0.0001774543,0.0002872288,0.00008186564,0.00003942613,0.00006184732,0.000292902,0.0001522386,0.00002534498],"category_scores_gemma":[0.001836674,0.0001771085,0.0002114952,0.00009882528,0.00005075679,0.000008790791,0.00008826167,0.0001968544,0.000006036841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005999891,"about_ca_system_score_gemma":0.0003535896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002672163,"about_ca_topic_score_gemma":0.000006035235,"domain_scores_codex":[0.9987687,0.00006623105,0.0004603812,0.0001935099,0.0002438292,0.0002673831],"domain_scores_gemma":[0.9984336,0.0002676064,0.0004109813,0.0003188104,0.0004209256,0.0001480629],"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":[0.00007802208,0.00007836219,0.01512291,0.00002215362,0.0001151021,0.0001155335,0.00002707239,0.01341584,0.96805,0.001004134,0.0004494239,0.001521414],"study_design_scores_gemma":[0.003058871,0.001707138,0.002274305,0.0002658452,0.0002698537,0.0006453658,0.0001207294,0.001760767,0.9275793,0.002567681,0.05904663,0.000703479],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8996632,0.003188691,0.09611875,0.0001135155,0.0005376389,0.0001776068,0.00005431669,0.000003357007,0.0001429183],"genre_scores_gemma":[0.9847565,0.001902335,0.01193859,0.0009999885,0.0003270259,0.000001712095,0.00002035691,0.00004065939,0.00001286895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08509326,"threshold_uncertainty_score":0.7222274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01753896807517896,"score_gpt":0.277257169101475,"score_spread":0.259718201026296,"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."}}