{"id":"W2106947130","doi":"10.1093/sysbio/syp054","title":"Species Trees from Highly Incongruent Gene Trees in Rice","year":2009,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Biology; Phylogenetic tree; Evolutionary biology; Inference; Tree (set theory); Bayesian probability; Phylogenetics; Gene; Computational biology; Pipeline (software); Supermatrix; Genetics; Artificial intelligence; Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002212987,0.0002150828,0.0004940304,0.00006881768,0.00004957454,0.00001815175,0.0002750701,0.0001915725,0.000007756259],"category_scores_gemma":[0.00009909363,0.0001687187,0.00009856352,0.00007868714,0.00007569373,6.800093e-7,0.0001134307,0.00006539946,0.00001622324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002268094,"about_ca_system_score_gemma":0.00003205243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001837572,"about_ca_topic_score_gemma":0.0007057593,"domain_scores_codex":[0.998565,0.0001939585,0.0004981179,0.0003986054,0.00006235678,0.0002820218],"domain_scores_gemma":[0.99927,0.00004005254,0.000156581,0.0004336765,0.00004676653,0.0000529131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002035198,0.0000635523,0.01262451,0.0001304972,0.00009060642,0.000003927413,0.0002139952,0.00005014059,0.9861116,0.0005525996,0.00006556993,0.00007260499],"study_design_scores_gemma":[0.001619828,0.0009903574,0.7815049,0.000451816,0.0001010194,0.00002210593,0.0008890154,0.0001420921,0.2056265,0.007330927,0.0006049864,0.0007163907],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906988,0.007138003,0.0002966282,0.0003217875,0.0002631996,0.0004053926,0.00004710235,0.000006884376,0.0008222181],"genre_scores_gemma":[0.998242,0.0002340705,0.0007404261,0.000303175,0.0002195264,0.00004703067,0.00005924639,0.000009852043,0.0001446621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7804851,"threshold_uncertainty_score":0.6880147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291836166448507,"score_gpt":0.2321676842736921,"score_spread":0.219249322609207,"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."}}