{"id":"W2987894624","doi":"10.1093/molbev/msz228","title":"On the Use of Information Criteria for Model Selection in Phylogenetics","year":2019,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Akaike information criterion; Bayesian information criterion; Model selection; Information Criteria; Bayes factor; Divergence (linguistics); Bayes' theorem; Selection (genetic algorithm); Statistics; Bayesian probability; Biology; Mathematics; Computer science; Econometrics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07253943,0.003111673,0.004090993,0.007570965,0.001948703,0.006967896,0.004292135,0.004335009,0.002481793],"category_scores_gemma":[0.2749398,0.001683458,0.003169386,0.007142113,0.008170336,0.0067,0.006820346,0.007324467,0.0009842968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004058416,"about_ca_system_score_gemma":0.00398171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00501565,"about_ca_topic_score_gemma":0.003298264,"domain_scores_codex":[0.9159233,0.06843613,0.003382036,0.003208316,0.008165795,0.0008843197],"domain_scores_gemma":[0.6551612,0.3169387,0.006758982,0.009990428,0.01007329,0.001077487],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001308858,0.0000654761,0.003418367,0.000953063,0.0007935987,0.0004999063,0.0006951882,0.3336811,0.001012763,0.5633177,0.004187139,0.09124482],"study_design_scores_gemma":[0.00003740211,0.00006238126,0.0006050747,0.0003788186,0.00006411316,0.0001355065,0.00006572883,0.4329833,0.0005993754,0.5618093,0.003162271,0.00009669365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002623157,0.002040653,0.9927158,0.0008708489,0.00008952287,0.00005469569,0.00008672113,0.0002158562,0.001302735],"genre_scores_gemma":[0.1734518,0.004176793,0.8167928,0.001502992,0.0006972381,0.000818436,0.0006414935,0.0008482498,0.001070121],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9274606,"threshold_uncertainty_score":0.3836297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584992803859321,"score_gpt":0.2543346152213883,"score_spread":0.2384846871827951,"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."}}