{"id":"W2152298208","doi":"10.1093/sysbio/syt022","title":"PhyloBayes MPI: Phylogenetic Reconstruction with Infinite Mixtures of Profiles in a Parallel Environment","year":2013,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":936,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Agriculture and Agri-Food Canada; Université de Montréal","funders":"","keywords":"Computer science; Dirichlet process; Phylogenomics; Hierarchical Dirichlet process; Dirichlet distribution; Gibbs sampling; Inference; Representation (politics); Tree (set theory); Phylogenetic tree; Algorithm; Theoretical computer science; Bayesian probability; Latent Dirichlet allocation; Mathematics; Artificial intelligence; Topic model; Combinatorics; Biology; Boundary value problem","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":[0.003308003,0.002867989,0.002688462,0.001829363,0.001717222,0.002761444,0.005769577,0.002027035,0.03997354],"category_scores_gemma":[0.01192642,0.002518424,0.002308426,0.00252011,0.001146087,0.003001639,0.004661057,0.004978016,0.02063872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120567,"about_ca_system_score_gemma":0.002591114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005633899,"about_ca_topic_score_gemma":0.005914317,"domain_scores_codex":[0.998576,0.0004500232,0.0001009468,0.0002694204,0.0004192714,0.0001842624],"domain_scores_gemma":[0.9977564,0.001012658,0.0001369916,0.00058287,0.0002863314,0.0002247983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003707623,0.0006022731,0.007486405,0.00280599,0.001460968,0.001603035,0.002390389,0.1430506,0.026868,0.09280628,0.3503502,0.3668682],"study_design_scores_gemma":[0.001286595,0.0001047925,0.002274436,0.0002317218,0.0001751455,0.0003826766,0.0001717389,0.750246,0.01327947,0.1070099,0.1245707,0.0002669087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009579464,0.0005366821,0.7212616,0.0005706527,0.0003748074,0.0001726343,0.008535074,0.2520038,0.006965335],"genre_scores_gemma":[0.08989586,0.0006856378,0.8215361,0.0004043306,0.0001768363,0.001826362,0.02055412,0.05813931,0.006781418],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03997354,"threshold_uncertainty_score":0.1337247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132984968193786,"score_gpt":0.22191598189564,"score_spread":0.2105861322137021,"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."}}