{"id":"W2154518589","doi":"10.1093/bioinformatics/btu181","title":"geiger v2.0: an expanded suite of methods for fitting macroevolutionary models to phylogenetic trees","year":2014,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":1222,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Geiger counter; Computer science; Source code; R package; Phylogenetic tree; Suite; Scope (computer science); Code (set theory); Data mining; Data science; Biology; Set (abstract data type); Programming language; Genetics; Physics; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008890259,0.004873794,0.003678935,0.005338884,0.001761308,0.003550969,0.007712415,0.002816166,0.05650549],"category_scores_gemma":[0.03033641,0.003871606,0.00695231,0.004257701,0.001083591,0.003303923,0.005129053,0.006761065,0.04635177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036789,"about_ca_system_score_gemma":0.002877613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004434432,"about_ca_topic_score_gemma":0.007304109,"domain_scores_codex":[0.9969922,0.001378086,0.000316641,0.0006325529,0.0004939442,0.0001865157],"domain_scores_gemma":[0.9905576,0.00698856,0.0005490779,0.001118855,0.0005877671,0.0001981333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000561489,0.0001680267,0.01079552,0.004648806,0.003669274,0.001286878,0.001489794,0.1142331,0.0107161,0.02919447,0.5847337,0.2385028],"study_design_scores_gemma":[0.0004502577,0.0001983881,0.00722422,0.0008087683,0.0008758333,0.002166772,0.000210216,0.4508587,0.009643701,0.0969108,0.4300638,0.0005885188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005276646,0.001498507,0.787264,0.0005369735,0.0003907423,0.0003424676,0.03946099,0.1608753,0.004354485],"genre_scores_gemma":[0.0219149,0.001068294,0.8013595,0.0005681629,0.0001475403,0.002028944,0.05111682,0.1174411,0.004354846],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05650549,"threshold_uncertainty_score":0.1890297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06591234001703411,"score_gpt":0.3228357091837009,"score_spread":0.2569233691666668,"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."}}