{"id":"W2952902141","doi":"10.1002/ece3.5185","title":"Tree shape‐based approaches for the comparative study of cophylogeny","year":2019,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"AIDS Vancouver; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Genomics; Ontario Genomics Institute; Genome Canada","keywords":"Coevolution; Tree (set theory); Approximate Bayesian computation; Phylogenetic tree; Bayesian probability; Host (biology); Kernel (algebra); Cluster analysis; Computer science; Statistics; Machine learning; Artificial intelligence; Biology; Mathematics; Evolutionary biology; Ecology; Inference; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000156311,0.00007063244,0.0001110987,0.00002130413,0.00008346748,0.000002834392,0.00007735456,0.00009149847,0.00001316569],"category_scores_gemma":[0.0000173913,0.00005364656,0.00003459226,0.00003945097,0.00008962747,0.000001346427,0.00003265181,0.00003833493,0.000003701698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007109269,"about_ca_system_score_gemma":0.00003625801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006552526,"about_ca_topic_score_gemma":0.0004915784,"domain_scores_codex":[0.9995061,0.00006061198,0.0001174626,0.000174807,0.00003761014,0.0001033867],"domain_scores_gemma":[0.9996686,0.00004932257,0.00006521195,0.0001527819,0.00004613856,0.00001791704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001433793,0.001459133,0.8616075,0.00007904337,0.0004475778,2.56095e-7,0.0009249278,0.02837148,0.09627008,0.004721726,0.003252642,0.001431856],"study_design_scores_gemma":[0.001547508,0.001854498,0.8527643,0.000001300136,0.00003969916,0.000001669579,0.001882546,0.1407256,0.0004745345,0.0001538349,0.0004741874,0.00008033912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944056,0.0003427202,0.004019532,0.00008704334,0.0001280476,0.0006339091,0.000009889131,0.000003519177,0.0003697031],"genre_scores_gemma":[0.9992773,0.000007120503,0.0002271283,0.00005082794,0.00003612252,0.00005869094,0.0000354274,0.000004230949,0.00030318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1123541,"threshold_uncertainty_score":0.2187643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02766402363529723,"score_gpt":0.2640524593277896,"score_spread":0.2363884356924924,"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."}}