{"id":"W2969864229","doi":"10.1093/molbev/msz182","title":"NUQA: Estimating Cancer Spatial and Temporal Heterogeneity and Evolution through Alignment-Free Methods","year":2019,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Cancer Research UK","keywords":"Biology; Phylogenetic tree; Hellinger distance; Metric (unit); Computational biology; Exome; Evolutionary biology; Bioinformatics; Exome sequencing; Genetics; Mutation; Statistics; Gene; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005885612,0.0008024505,0.001186766,0.003363879,0.001185698,0.001675099,0.001680587,0.001332572,0.001706797],"category_scores_gemma":[0.01621361,0.0006052257,0.001346941,0.002162726,0.0008297228,0.001619667,0.00213832,0.001770221,0.0005653244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488144,"about_ca_system_score_gemma":0.001948256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009294347,"about_ca_topic_score_gemma":0.01311793,"domain_scores_codex":[0.9980483,0.0007633288,0.0001534749,0.0005605801,0.0003739136,0.0001003132],"domain_scores_gemma":[0.994087,0.003872446,0.000694969,0.0006170433,0.0005191162,0.0002094047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008098093,0.0002745404,0.06892764,0.0008025947,0.001878749,0.0005916064,0.001509486,0.4974541,0.04274496,0.02115217,0.01063731,0.3532171],"study_design_scores_gemma":[0.00003682337,0.00007550898,0.007837821,0.00002319796,0.00004826365,0.0002157598,0.0001199441,0.9677219,0.005072852,0.01458027,0.004215521,0.00005216983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07807555,0.0006002166,0.9146606,0.0002293383,0.00006421241,0.0000849244,0.001558204,0.004273493,0.0004534874],"genre_scores_gemma":[0.3126238,0.0002328678,0.6803237,0.0001609372,0.00005125077,0.0002795306,0.004188327,0.001090848,0.001048801],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009294347,"threshold_uncertainty_score":0.0311265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0115944409139092,"score_gpt":0.3116206867120703,"score_spread":0.3000262457981611,"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."}}