{"id":"W4404860583","doi":"10.1038/s41559-024-02599-y","title":"Environmental filtering, not dispersal history, explains global patterns of phylogenetic turnover in seed plants at deep evolutionary timescales","year":2024,"lang":"en","type":"article","venue":"Nature Ecology & Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Akademie Věd České Republiky; Austrian Science Fund; Grantová Agentura České Republiky; Deutsche Forschungsgemeinschaft; University of Alberta; Government of Canada","keywords":"Biological dispersal; Phylogenetic tree; Ecology; Biodiversity; Beta diversity; Biology; Phylogenetic diversity; Seed dispersal; Range (aeronautics); Evolutionary ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001304899,0.0001882231,0.0002080499,0.00007573258,0.00009807054,0.000002747872,0.0001661222,0.0004669935,0.001555205],"category_scores_gemma":[0.00002059686,0.0001906127,0.00008215392,0.00008225169,0.0003431185,0.0001332961,0.0002148681,0.0003506047,0.0003200502],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004746038,"about_ca_system_score_gemma":0.00001997066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000760285,"about_ca_topic_score_gemma":0.01258055,"domain_scores_codex":[0.9986454,0.0001046289,0.0002777705,0.0004501679,0.0001945721,0.0003274756],"domain_scores_gemma":[0.9996167,0.0001012983,0.00008238847,0.0001456473,0.000003363224,0.00005057633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007188888,0.0001330075,0.988909,0.00001970231,0.00004117581,0.00003047988,0.0005599526,0.002486353,0.006285263,0.0003225507,0.001045999,0.00009463538],"study_design_scores_gemma":[0.0003306862,0.0001012602,0.9751839,0.00001615868,0.00002544228,0.00004867906,0.00007845847,0.0223941,0.00006788817,0.0002206516,0.001368492,0.000164303],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946004,0.002569638,0.0002711335,0.0001492635,0.001232208,0.0002037673,0.0001568251,0.00003877548,0.000778015],"genre_scores_gemma":[0.9988915,0.0001093038,0.0001702542,0.0001139782,0.00004779541,0.00003570976,0.00008947857,0.00001161424,0.0005304202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01990775,"threshold_uncertainty_score":0.9993575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00391866013794065,"score_gpt":0.2041059382274645,"score_spread":0.2001872780895238,"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."}}