{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003206282,0.000779577,0.001215388,0.007039772,0.001213123,0.002184569,0.001727992,0.001335081,0.001671012],"category_scores_gemma":[0.02816324,0.0008427696,0.001339633,0.004501024,0.001091833,0.002372082,0.002560524,0.001973566,0.0006093006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380795,"about_ca_system_score_gemma":0.001306459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008935496,"about_ca_topic_score_gemma":0.008858016,"domain_scores_codex":[0.9972711,0.001229343,0.0001437472,0.0007069511,0.0005148909,0.0001340026],"domain_scores_gemma":[0.9868746,0.009443979,0.001170187,0.001214982,0.0009894127,0.0003068433],"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":[0.000142923,0.0001417457,0.03160335,0.000213456,0.0004999642,0.0002958681,0.0006324028,0.7723445,0.004731912,0.04757162,0.00212291,0.1396993],"study_design_scores_gemma":[0.00001748945,0.00001367472,0.002908914,0.00001536612,0.0000177533,0.00006064178,0.00005785828,0.9516903,0.0005636945,0.04397031,0.0006622211,0.0000218001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09005663,0.0002309467,0.9075063,0.0001945946,0.00001544296,0.00006499053,0.0005155223,0.0006275246,0.0007880727],"genre_scores_gemma":[0.4941384,0.0002288993,0.502688,0.00009881897,0.00003463696,0.000187098,0.001691878,0.0001925409,0.0007397223],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008935496,"threshold_uncertainty_score":0.01776701,"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."}}