{"id":"W3159758719","doi":"10.1089/cmb.2020.0375","title":"Estimating Genetic Similarity Matrices Using Phylogenies","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Phylogenetic tree; Similarity (geometry); Genetic similarity; Heritability; Biology; Tree (set theory); Genotype; Genetic analysis; Distance matrices in phylogeny; Evolutionary biology; Statistics; Genetics; Mathematics; Computer science; Artificial intelligence; Genetic diversity; Bioinformatics; Gene; Combinatorics; Population","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":[0.00009436431,0.00007421018,0.0001300761,0.00004806475,0.00007758029,0.00001744764,0.0001013043,0.00009792064,0.00003748163],"category_scores_gemma":[0.00009681866,0.00007046502,0.00009333498,0.00007807499,0.00004974741,0.00000348147,0.00006205443,0.00007378589,0.000001597851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008260183,"about_ca_system_score_gemma":0.0001731357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001693733,"about_ca_topic_score_gemma":0.000001224174,"domain_scores_codex":[0.999364,0.00009184481,0.000257649,0.0001099338,0.00008179923,0.00009476039],"domain_scores_gemma":[0.9991909,0.0000285729,0.0002475501,0.00006319883,0.0004243948,0.00004538707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00005506401,0.00004207999,0.0657907,0.00001777273,0.0001496976,0.00002458202,0.0000689746,0.7969459,0.130275,0.0003051486,0.0004615224,0.005863486],"study_design_scores_gemma":[0.005650138,0.001715468,0.6160687,0.0001210879,0.0005344181,0.011031,0.000618772,0.08636752,0.07494018,0.1346157,0.06692444,0.001412606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8933573,0.001530324,0.1044946,0.0001196828,0.0003976655,0.00001921259,0.000015198,0.000001652856,0.00006432141],"genre_scores_gemma":[0.782907,0.00002060445,0.216434,0.0002199721,0.0003602639,9.284272e-8,0.00003867523,0.000003640597,0.00001578723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7105784,"threshold_uncertainty_score":0.287348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016111658881796,"score_gpt":0.2904591659925219,"score_spread":0.2702980494037039,"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."}}