{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001188879,0.0001657387,0.0002037151,0.00005131184,0.0001019534,0.000005442873,0.0001763963,0.0001566918,0.000003966605],"category_scores_gemma":[0.00005207232,0.0001440926,0.00003003223,0.00005814147,0.0003463331,0.000004732949,0.0003324322,0.00005903771,5.998454e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009882957,"about_ca_system_score_gemma":0.00009290555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004069047,"about_ca_topic_score_gemma":0.0001187012,"domain_scores_codex":[0.998899,0.0001067616,0.0002472479,0.0004965438,0.00005484157,0.0001956221],"domain_scores_gemma":[0.999374,0.00003437597,0.0001248563,0.0003434443,0.00006916656,0.00005410496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006249378,0.00004350849,0.08519254,0.00002165301,0.0001107022,8.779225e-8,0.00004294963,0.0007328161,0.9098048,0.0007689423,0.0000210523,0.003198465],"study_design_scores_gemma":[0.001335397,0.0009197675,0.758833,0.00004260399,0.0001775498,0.00003152417,0.0001469434,0.1492678,0.01723361,0.07071593,0.000618918,0.0006769371],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9162366,0.01614139,0.06687473,0.0001678011,0.0000211512,0.0002181143,0.0002379897,0.000003632627,0.00009857703],"genre_scores_gemma":[0.9720167,0.001180632,0.02643376,0.00004789178,0.00009905997,0.00001842671,0.0001600989,0.000009857216,0.00003360469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8925712,"threshold_uncertainty_score":0.5875925,"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."}}