{"id":"W4376959339","doi":"10.1111/2041-210x.14128","title":"E<scp>vo</scp>P<scp>hylo</scp>: An <scp>r</scp> package for pre‐ and postprocessing of morphological data from relaxed clock Bayesian phylogenetics","year":2023,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Harvard University","keywords":"Bayesian probability; Phylogenetic tree; Inference; Molecular clock; Bayes' theorem; Phylogenetics; Computer science; Character evolution; Range (aeronautics); Character (mathematics); Lineage (genetic); Bayesian inference; Biology; Evolutionary biology; Macroevolution; R package; Artificial intelligence; Clade; Mathematics; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00554933,0.003722315,0.003261535,0.003303573,0.001404296,0.003965459,0.005605785,0.00153571,0.2881604],"category_scores_gemma":[0.02537813,0.00293622,0.003479456,0.003457527,0.001865271,0.00342035,0.004741947,0.004915884,0.1884609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012574,"about_ca_system_score_gemma":0.003285632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004314733,"about_ca_topic_score_gemma":0.005852121,"domain_scores_codex":[0.9975322,0.0005849015,0.0002451375,0.0006497698,0.0007382202,0.0002497851],"domain_scores_gemma":[0.989126,0.006165884,0.001208608,0.001626391,0.001423136,0.0004500221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003088813,0.00007562841,0.002844208,0.002617131,0.0004057014,0.0003919459,0.0004420271,0.004303908,0.004333135,0.015261,0.9201676,0.0488488],"study_design_scores_gemma":[0.0006639052,0.0001217004,0.009117469,0.001110494,0.0003086322,0.0009266972,0.0001388247,0.03640091,0.01811369,0.05540917,0.8772469,0.0004415827],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002416846,0.00066596,0.3459045,0.001060965,0.0006308695,0.0004447079,0.1693874,0.4680121,0.01147665],"genre_scores_gemma":[0.02021169,0.0006489374,0.3495314,0.001748294,0.0002579793,0.003214284,0.1192779,0.4903639,0.01474562],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.2881604,"threshold_uncertainty_score":0.9639926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06881984864156905,"score_gpt":0.3566751468322568,"score_spread":0.2878552981906877,"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."}}