{"id":"W3174244217","doi":"10.1093/sysbio/syab049","title":"Unifying Phylogenetic Birth–Death Models in Epidemiology and Macroevolution","year":2021,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"AIDS Vancouver; University of Toronto; Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; University of Toronto","keywords":"Macroevolution; Birth–death process; Inference; Unification; Biology; Sampling (signal processing); Phylogenetic tree; Range (aeronautics); Evolutionary biology; Process (computing); Computer science; Artificial intelligence; Genetics; Demography; Population","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":[],"consensus_categories":[],"category_scores_codex":[0.01901069,0.0008022988,0.001220165,0.002102579,0.0009024109,0.002111194,0.002911497,0.002697678,0.001919431],"category_scores_gemma":[0.04023961,0.0006746414,0.001590953,0.001897333,0.00447286,0.005975629,0.003086062,0.003158304,0.000417761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00211846,"about_ca_system_score_gemma":0.001586435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003445996,"about_ca_topic_score_gemma":0.003619461,"domain_scores_codex":[0.9943879,0.004122501,0.0002142977,0.0005013272,0.0005388056,0.0002350801],"domain_scores_gemma":[0.968447,0.0267534,0.002110427,0.001408635,0.0008914691,0.0003891859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008818361,0.00001450478,0.001773703,0.00006318962,0.00003042919,0.00006369859,0.0002963629,0.04514341,0.0001403753,0.9430721,0.0004772426,0.008916155],"study_design_scores_gemma":[0.000007878056,0.00001780651,0.0006552981,0.00004177909,0.00001418621,0.00007662932,0.00005831474,0.1772116,0.0001042169,0.8196905,0.002101667,0.00002020542],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01441655,0.001607514,0.9786133,0.002539084,0.0001118172,0.00004337387,0.000112871,0.00007254321,0.002482824],"genre_scores_gemma":[0.6350903,0.005778811,0.3507889,0.001738631,0.0007499748,0.0003424406,0.0003306768,0.0001074172,0.005072858],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01901069,"threshold_uncertainty_score":0.1005393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07713335066736088,"score_gpt":0.2857222887741143,"score_spread":0.2085889381067534,"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."}}