{"id":"W2144029912","doi":"10.1093/sysbio/syr065","title":"Fast Bayesian Choice of Phylogenetic Models: Prospecting Data Augmentation–Based Thermodynamic Integration","year":2011,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; McGill University; Agriculture and Agri-Food Canada","funders":"","keywords":"Atmospheric research; Bayesian probability; Marie curie; Library science; Research center; Phylogenetic tree; Agriculture; Prospecting; Bayesian inference; Biodiversity; Center (category theory); Biology; Agricultural economics; Archaeology; Statistics; Geography; Ecology; Mathematics; Computer science; Political science; Engineering; Economics; Genetics; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01195224,0.001411102,0.002902437,0.002538509,0.001189229,0.00270699,0.004321021,0.002326643,0.007445871],"category_scores_gemma":[0.05086533,0.001925077,0.001931668,0.002000299,0.001691008,0.004902783,0.005607127,0.004552663,0.002063333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001367993,"about_ca_system_score_gemma":0.002648885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003453511,"about_ca_topic_score_gemma":0.004813536,"domain_scores_codex":[0.996492,0.00231479,0.0001397045,0.0002935384,0.0006193335,0.0001405582],"domain_scores_gemma":[0.982808,0.01371407,0.0006496121,0.001085593,0.001306593,0.0004361275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004193192,0.0001595464,0.004246462,0.0005806888,0.0001802203,0.0004439531,0.0005574588,0.6574905,0.00286656,0.1689173,0.004461,0.1596771],"study_design_scores_gemma":[0.00001943337,0.00001479947,0.0001136336,0.00003915829,0.000009397648,0.00003050445,0.00001651602,0.9474054,0.0003052352,0.05092181,0.001104478,0.00001956219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01252532,0.0005223188,0.983447,0.000464267,0.00006261704,0.00009394789,0.0001264574,0.000903675,0.001854414],"genre_scores_gemma":[0.1810449,0.000641128,0.8142545,0.0004857414,0.0001443958,0.0004969649,0.0005753582,0.0007012436,0.001655855],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01195224,"threshold_uncertainty_score":0.06321025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06833684578545228,"score_gpt":0.2860064725691254,"score_spread":0.2176696267836731,"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."}}