{"id":"W2100728353","doi":"10.1093/sysbio/syu098","title":"Among-Character Rate Variation Distributions in Phylogenetic Analysis of Discrete Morphological Characters","year":2014,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Log-normal distribution; Phylogenetic tree; Rate of evolution; Character (mathematics); Biology; Statistics; Bayesian probability; Mathematics; Distribution (mathematics); Evolutionary biology; 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":[0.06690796,0.002142616,0.003308881,0.009623976,0.002727504,0.005537255,0.005298486,0.003769872,0.004411093],"category_scores_gemma":[0.1768858,0.001660455,0.005413676,0.01258378,0.007212472,0.009091676,0.004547962,0.008543067,0.001666823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003074881,"about_ca_system_score_gemma":0.001222474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002898795,"about_ca_topic_score_gemma":0.002917819,"domain_scores_codex":[0.9278794,0.04523041,0.004374351,0.01657239,0.004999863,0.0009435673],"domain_scores_gemma":[0.870494,0.0980233,0.01101613,0.01656696,0.003075807,0.0008237918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008448861,0.0004009563,0.3830178,0.002562389,0.006368133,0.002170642,0.00639671,0.2522517,0.01620875,0.1440179,0.005525374,0.1802348],"study_design_scores_gemma":[0.0001431867,0.0004013199,0.08327323,0.0006292837,0.000766981,0.002676376,0.001470545,0.5554531,0.005383306,0.333088,0.0161391,0.0005755631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1779969,0.002815244,0.8090752,0.0006365975,0.0001694435,0.0005667758,0.002277181,0.001548696,0.004913899],"genre_scores_gemma":[0.7578824,0.0008624039,0.2333281,0.0004700269,0.0001299716,0.001238673,0.00410991,0.001086929,0.0008916496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06690796,"threshold_uncertainty_score":0.3538473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415780564100818,"score_gpt":0.232839651240368,"score_spread":0.2186818455993599,"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."}}