{"id":"W2036272181","doi":"10.1093/molbev/msi123","title":"Likelihood, Parsimony, and Heterogeneous Evolution","year":2005,"lang":"en","type":"letter","venue":"Molecular Biology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Genome Atlantic; Genome Canada","keywords":"Phylogenetic tree; Maximum parsimony; Biology; Tree rearrangement; Maximum likelihood; Range (aeronautics); Nonparametric statistics; Tree (set theory); Statistics; Phylogenetics; Evolutionary biology; Mathematics; Genetics; Clade; Combinatorics; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001983407,0.0003600273,0.0003952701,0.0001921749,0.0003691469,0.0000259299,0.0001327971,0.00124898,0.0001405034],"category_scores_gemma":[0.00004446727,0.0003227508,0.00008942923,0.0001082181,0.000595892,0.00007143467,0.00003577908,0.0007849904,0.0001176841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002311139,"about_ca_system_score_gemma":0.00004918407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00103918,"about_ca_topic_score_gemma":0.006473422,"domain_scores_codex":[0.9980118,0.0003406354,0.0002849963,0.0006541863,0.000119306,0.0005890538],"domain_scores_gemma":[0.9993951,0.00009202789,0.0001459775,0.0002176079,0.00005450152,0.00009474446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006372191,0.00001486181,0.8320873,0.00009807397,0.000296773,0.0001894474,0.00007259796,0.00007553137,0.0001267539,0.0004563263,0.1558647,0.01065394],"study_design_scores_gemma":[0.0006897141,0.0005249864,0.5406516,0.00005761388,0.0002781941,0.0006223538,0.00004300131,0.002327432,0.00001748479,0.01828293,0.4355399,0.0009648449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2148218,0.3052576,0.01353562,0.4504224,0.002672851,0.001094346,0.0007305457,0.0004126969,0.01105213],"genre_scores_gemma":[0.89363,0.001327582,0.00053245,0.1019749,0.001235613,0.000007773384,0.0009721604,0.00001099854,0.0003085732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6788082,"threshold_uncertainty_score":0.9999225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007910423874856569,"score_gpt":0.2238510604297878,"score_spread":0.2159406365549312,"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."}}