{"id":"W4302025018","doi":"10.1101/2022.10.01.510440","title":"Topological incongruence between Median-Joining Networks and Bayesian inference phylogenies","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Phylogenetic tree; Inference; Bayesian probability; Biology; Evolutionary biology; Phylogenetics; Statistical hypothesis testing; Branching (polymer chemistry); Character (mathematics); Bayesian inference; Computer science; Artificial intelligence; Statistics; Mathematics","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":[0.02643251,0.0005593211,0.0009438085,0.007472842,0.002069505,0.003324826,0.001830597,0.001440195,0.00380804],"category_scores_gemma":[0.1356217,0.0004803286,0.0009339364,0.004490884,0.0037914,0.003096879,0.002044065,0.001499084,0.0003620968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135028,"about_ca_system_score_gemma":0.0006008762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001087028,"about_ca_topic_score_gemma":0.001277645,"domain_scores_codex":[0.9750267,0.0159999,0.001568184,0.003230421,0.003484843,0.0006899463],"domain_scores_gemma":[0.8083705,0.1702758,0.01038228,0.0057906,0.003673249,0.001507504],"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":[0.002130304,0.0001874736,0.6272841,0.001462229,0.00313913,0.001432956,0.006064997,0.1437683,0.008424687,0.09981485,0.002663469,0.1036275],"study_design_scores_gemma":[0.0001432679,0.0003210997,0.1415488,0.0003043682,0.0004684382,0.001601067,0.003191288,0.5805547,0.005917558,0.2620788,0.00370312,0.0001675463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8601011,0.001083257,0.131709,0.0003416099,0.00004657994,0.00008622856,0.0006516765,0.0002626555,0.005717982],"genre_scores_gemma":[0.9818667,0.00009479792,0.01727335,0.00004609945,0.00002754155,0.00004341465,0.0004885694,0.00003056036,0.0001288267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02643251,"threshold_uncertainty_score":0.1397902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01495112624990766,"score_gpt":0.2363703541444059,"score_spread":0.2214192278944983,"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."}}