{"id":"W2991196083","doi":"10.1142/9789811215636_0022","title":"TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies","year":2019,"lang":"en","type":"article","venue":"","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Ontario Institute for Cancer Research; University of Toronto","funders":"National Cancer Institute","keywords":"Mutation; Allele; Allele frequency; Genetics; Computer science; Biology; Gene","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":[0.00004602239,0.00007640312,0.00006059162,0.00002941699,0.00003928529,0.00002402825,0.00004332668,0.00008213739,0.0001834768],"category_scores_gemma":[0.00003583237,0.00007151751,0.0000334494,0.0000281968,0.00003720421,0.000001904013,0.0000126931,0.00004870127,0.00001295817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008939345,"about_ca_system_score_gemma":0.00005896403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002836914,"about_ca_topic_score_gemma":0.0001152728,"domain_scores_codex":[0.9995575,0.00001112205,0.00008092453,0.0001938645,0.00005588258,0.0001007364],"domain_scores_gemma":[0.9997283,0.00003109508,0.00002689676,0.0001359647,0.00003701209,0.00004070214],"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":[0.0002511867,0.0001361406,0.02267155,0.00004670058,0.00007250259,0.000006982274,0.00005321329,0.01317532,0.9168844,0.008366511,0.01831279,0.0200227],"study_design_scores_gemma":[0.004981508,0.003420805,0.09271159,0.00004657328,0.00007647696,0.00009353368,0.0007989671,0.01595181,0.7218533,0.003241293,0.1554538,0.001370335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888658,0.0003626528,0.0008600022,0.0003258677,0.0001637647,0.0001309144,0.00003766937,0.000009294069,0.009244052],"genre_scores_gemma":[0.9961557,0.00007358933,0.001841557,0.001016963,0.00008546054,0.000008109775,0.0001402449,0.000008996737,0.0006693906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1950311,"threshold_uncertainty_score":0.29164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004855298977570623,"score_gpt":0.2103844300030203,"score_spread":0.2055291310254497,"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."}}