{"id":"W2051062503","doi":"10.1093/sysbio/syu099","title":"Bayesian Long Branch Attraction Bias and Corrections","year":2014,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Attraction; Bayesian probability; Tree (set theory); Set (abstract data type); Star (game theory); Bayesian network; Biology; Computer science; Mathematics; Statistics; Algorithm; Statistical physics; Physics; Combinatorics; Mathematical analysis","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":[0.03012596,0.0009983421,0.001747534,0.002407568,0.0014087,0.002845564,0.003557529,0.002391763,0.01055112],"category_scores_gemma":[0.2859015,0.0009400204,0.0008802103,0.0022714,0.003190917,0.004325095,0.003270774,0.0051899,0.002120371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002430649,"about_ca_system_score_gemma":0.00187344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00340389,"about_ca_topic_score_gemma":0.003781922,"domain_scores_codex":[0.9786916,0.01199544,0.0008707223,0.003024769,0.004889131,0.0005283891],"domain_scores_gemma":[0.8605815,0.1064277,0.006152885,0.0140365,0.01145874,0.001342745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003659659,0.00007316441,0.01542854,0.0005535783,0.0003710465,0.0005288501,0.00088841,0.09534293,0.002366092,0.6309045,0.02344453,0.2297325],"study_design_scores_gemma":[0.00005605497,0.00004160161,0.003630402,0.0002014369,0.00006884885,0.0006260547,0.0001074573,0.2155708,0.001787829,0.7638854,0.01391596,0.000108087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03390535,0.00278677,0.9390455,0.004997347,0.001300158,0.0001284279,0.0003860483,0.001734052,0.01571638],"genre_scores_gemma":[0.6324465,0.001396034,0.3482087,0.003171467,0.001241686,0.0004007691,0.00052575,0.001431533,0.01117771],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03012596,"threshold_uncertainty_score":0.1593232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763570097442089,"score_gpt":0.2473932853863419,"score_spread":0.2297575844119211,"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."}}