{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000773124,0.00101776,0.0006279118,0.001498549,0.0005657899,0.00151727,0.001496778,0.00120908,0.003360179],"category_scores_gemma":[0.003691969,0.000672898,0.001081669,0.000884343,0.0005749908,0.0009139168,0.001412073,0.001156701,0.001183148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008116409,"about_ca_system_score_gemma":0.001443574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008028561,"about_ca_topic_score_gemma":0.01159445,"domain_scores_codex":[0.9996716,0.0000446724,0.00002400319,0.00009579051,0.0001215878,0.0000424145],"domain_scores_gemma":[0.9990393,0.000380673,0.0001259728,0.0001980668,0.0001812219,0.0000747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001055101,0.000206285,0.02174968,0.0004710984,0.000311612,0.0005756412,0.0009040402,0.3613391,0.1177198,0.01838476,0.01435177,0.4629311],"study_design_scores_gemma":[0.00002397977,0.00004689605,0.001639312,0.00001579841,0.00002064723,0.0001501425,0.00007601897,0.9623713,0.02657874,0.003942473,0.00510196,0.00003270009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04873719,0.0001026548,0.9404337,0.0001200227,0.00004561895,0.00009752307,0.001020009,0.008306772,0.001136586],"genre_scores_gemma":[0.214832,0.0001986259,0.7755274,0.00008540845,0.00002099117,0.0001563538,0.004069586,0.002361545,0.002748022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008028561,"threshold_uncertainty_score":0.01596367,"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."}}