{"id":"W4214515118","doi":"10.1111/geb.13471","title":"Environmental filtering drives assembly of diatom communities over evolutionary time‐scales","year":2022,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Museum of Nature","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Deutsche Forschungsgemeinschaft; Natural Environment Research Council; Sight Research UK","keywords":"Ecology; Species richness; Phylogenetic tree; Community structure; Biology; Extinction (optical mineralogy); Taxon; Macroevolution; Competition (biology); Community; Macroecology; Niche; Phylogenetics; Ecosystem; Paleontology","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":[0.0006421354,0.0001479454,0.000241124,0.000613721,0.0005227988,0.0008241314,0.0003170155,0.0003184981,0.001121189],"category_scores_gemma":[0.001952514,0.0002025558,0.0002256552,0.0003535333,0.0004778078,0.0005191532,0.0005343166,0.0003077061,0.0001711496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005186237,"about_ca_system_score_gemma":0.0002160442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002008865,"about_ca_topic_score_gemma":0.003476811,"domain_scores_codex":[0.9997994,0.00003400799,0.00001286898,0.00009102841,0.00002935499,0.0000333735],"domain_scores_gemma":[0.9988245,0.0002900822,0.0004843886,0.0000941532,0.0001524384,0.0001544889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001354168,0.00006031054,0.8270013,0.0001519213,0.0002102934,0.0002254936,0.000870181,0.006699329,0.1412722,0.002237962,0.0002767913,0.02085872],"study_design_scores_gemma":[0.000003294998,0.00005997674,0.9799582,0.000007888566,0.00002775626,0.0001132503,0.0002110024,0.01565012,0.002545263,0.0009702598,0.0004383379,0.00001463406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976277,0.000131377,0.001730575,0.00002819923,0.000001614745,0.000003242919,0.00008860745,0.0000150981,0.0003735868],"genre_scores_gemma":[0.9992203,0.00003507773,0.0005581076,0.000007933379,0.000002375046,0.000003404183,0.0000683558,0.000002849954,0.0001016521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002008865,"threshold_uncertainty_score":0.003994346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006278176303362019,"score_gpt":0.2264700714669164,"score_spread":0.2201918951635544,"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."}}