{"id":"W2121270248","doi":"10.1186/1471-2148-5-8","title":"Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation","year":2005,"lang":"en","type":"article","venue":"BMC Evolutionary Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Bayesian probability; Inference; Bayesian inference; Posterior probability; Phylogenetic tree; Statistics; Sequence (biology); Mathematics; Tree (set theory); Biology; Bayesian statistics; Algorithm; Artificial intelligence; Computer science; Combinatorics; Genetics","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":[0.09264179,0.001528364,0.002578281,0.004531096,0.002136366,0.005252497,0.003166724,0.003455065,0.002210993],"category_scores_gemma":[0.3266939,0.001840372,0.002724983,0.004396993,0.005312702,0.00880117,0.003618643,0.004838367,0.0007211764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002812276,"about_ca_system_score_gemma":0.001858482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001999247,"about_ca_topic_score_gemma":0.001844801,"domain_scores_codex":[0.9401875,0.04718321,0.00272421,0.004135868,0.004841988,0.0009271434],"domain_scores_gemma":[0.6384067,0.3231409,0.02009736,0.01130612,0.005469345,0.001579473],"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":[0.001639506,0.0001936428,0.0623409,0.001311486,0.001743249,0.0006385397,0.00209734,0.7880069,0.008031909,0.06179367,0.001261682,0.07094111],"study_design_scores_gemma":[0.0001039483,0.0002061677,0.01222959,0.0001880379,0.0001828385,0.0005523452,0.0002263813,0.8364543,0.00368262,0.1448742,0.001109396,0.000190141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2017834,0.001078954,0.7937695,0.000704876,0.00004402959,0.0001280022,0.0005998155,0.000559916,0.001331432],"genre_scores_gemma":[0.7614272,0.0006259641,0.2350218,0.0002816683,0.00009854585,0.0003816416,0.0015239,0.0003588625,0.0002805004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09264179,"threshold_uncertainty_score":0.4899424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06227741912597764,"score_gpt":0.3084717635559375,"score_spread":0.2461943444299598,"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."}}