{"id":"W4254394809","doi":"10.1158/1538-7445.compsysbio-b2-59","title":"Abstract B2-59: PhyloSpan: Using multi-mutation reads to resolve subclonal architectures from heterogeneous tumor samples","year":2015,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; Genetics; Indel; Germline mutation; Somatic cell; Germline; Computational biology; Mutation; Genotype; Single-nucleotide polymorphism; 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":[0.002723796,0.001005783,0.0008431965,0.002335683,0.001129597,0.001523513,0.001444107,0.001170372,0.005897274],"category_scores_gemma":[0.004475636,0.0007920295,0.001060154,0.00140211,0.0005728408,0.0008726274,0.001347413,0.001410512,0.003350159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005832518,"about_ca_system_score_gemma":0.0009382179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002618528,"about_ca_topic_score_gemma":0.004906069,"domain_scores_codex":[0.9990471,0.0001805827,0.00006812622,0.0003587049,0.0002742266,0.00007124609],"domain_scores_gemma":[0.998021,0.0007860799,0.000248002,0.0003662182,0.0004234045,0.000155275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002939088,0.0003348865,0.03416149,0.001252833,0.0006226118,0.001460604,0.0008128269,0.05732033,0.502174,0.006325628,0.02250088,0.370095],"study_design_scores_gemma":[0.0002224816,0.0002814091,0.021515,0.00008773387,0.0001265034,0.0009211708,0.0002307425,0.7084365,0.2332814,0.00898271,0.02576826,0.0001460448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2258579,0.0008377468,0.7224383,0.0004659127,0.0001880321,0.0003489658,0.01335195,0.03241233,0.004098928],"genre_scores_gemma":[0.1990449,0.0001605518,0.784079,0.000205978,0.00003640627,0.0002485323,0.01107502,0.002762762,0.002386908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005897274,"threshold_uncertainty_score":0.01972836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1389714530052669,"score_gpt":0.4069566911741654,"score_spread":0.2679852381688984,"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."}}