{"id":"W2969789886","doi":"","title":"Structural variation and fusion detection using targeted sequencing data from circulating cell free DNA","year":2019,"lang":"en","type":"article","venue":"PMC","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Structural variation; Computational biology; Contig; DNA sequencing; Liquid biopsy; Copy-number variation; Computer science; DNA; Biology; Breakpoint; Cell-free fetal DNA; Genome; Genetics; Cancer; Gene; Chromosomal translocation","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":[0.00006853903,0.00007631009,0.00006812454,0.00001657138,0.00006603801,0.00003604006,0.0001182036,0.00007955913,0.00001865329],"category_scores_gemma":[0.00007798756,0.00008149857,0.00001430452,0.00003267043,0.000009027919,0.000007909829,0.0002659996,0.0000458253,0.000002637812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000321984,"about_ca_system_score_gemma":0.00004497418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009668645,"about_ca_topic_score_gemma":0.0001331398,"domain_scores_codex":[0.9994268,0.00001774706,0.0001077072,0.0002852655,0.00006005502,0.0001023616],"domain_scores_gemma":[0.999418,0.00001789028,0.00007424945,0.0004297516,0.00002882619,0.00003127267],"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":[0.00001208459,0.000001733659,0.008202248,0.000008335541,0.000007959703,4.873032e-7,0.00007453108,0.000723821,0.9900166,0.000001446962,0.000008220691,0.0009425196],"study_design_scores_gemma":[0.0008742983,0.00007187033,0.07234617,0.00001985133,0.00004723932,0.000008640458,0.0001329393,0.1709721,0.754558,0.0004408107,0.0002656678,0.0002623488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995719,0.0005178835,0.003124766,0.000007859254,0.0003191026,0.00009973475,0.0001222553,0.000006459337,0.00008292811],"genre_scores_gemma":[0.996314,0.00004242983,0.002923364,0.00004173368,0.0002737252,7.352624e-7,0.0003821876,0.00001272575,0.000009035391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2354586,"threshold_uncertainty_score":0.3323415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02201407140156379,"score_gpt":0.2362575868536635,"score_spread":0.2142435154520997,"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."}}