{"id":"W2905547226","doi":"10.1016/j.jmoldx.2018.09.008","title":"Somatic Tumor Variant Filtration Strategies to Optimize Tumor-Only Molecular Profiling Using Targeted Next-Generation Sequencing Panels","year":2018,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Princess Margaret Cancer Foundation; Genome Canada","keywords":"Profiling (computer programming); Somatic cell; Computational biology; Biology; Genetics; Computer science; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001632667,0.0009289365,0.0006471552,0.001477249,0.000407019,0.001559048,0.0007195526,0.0006192939,0.001625728],"category_scores_gemma":[0.002810352,0.000431806,0.000819155,0.0008074571,0.0002485008,0.000831382,0.0009349941,0.0008844644,0.0009387737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004479,"about_ca_system_score_gemma":0.0009898782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001823663,"about_ca_topic_score_gemma":0.005106369,"domain_scores_codex":[0.9992746,0.000127747,0.0000461326,0.0002208133,0.0002316603,0.00009913505],"domain_scores_gemma":[0.999109,0.0003887118,0.00008776099,0.0001187121,0.0002372343,0.00005861069],"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":[0.0006803093,0.0003164716,0.02617531,0.0002766365,0.0004369337,0.0003896809,0.0001829256,0.03626258,0.5847999,0.005479556,0.004099467,0.3409002],"study_design_scores_gemma":[0.00007086001,0.0004404355,0.02463868,0.00005552109,0.0005745561,0.001730345,0.0001207611,0.4734848,0.4765049,0.01097589,0.0113053,0.00009795294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2352096,0.002006816,0.7540611,0.0004597648,0.000127088,0.0002423897,0.001489509,0.003287601,0.003116095],"genre_scores_gemma":[0.6037285,0.0008305733,0.3892324,0.0003589663,0.00007420245,0.0001574278,0.002817404,0.0004311722,0.002369317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001823663,"threshold_uncertainty_score":0.008634448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03405101440251263,"score_gpt":0.2704091746459187,"score_spread":0.2363581602434061,"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."}}