{"id":"W2810345475","doi":"10.1111/ddi.12812","title":"Functional diversity and redundancy of freshwater fish communities across biogeographic and environmental gradients","year":2018,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Fisheries and Oceans Canada; University of Toronto; Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Species richness; Ecology; Null model; Ecosystem; Species diversity; Biology; Functional diversity; Macroecology; Freshwater fish; Geography; Fish <Actinopterygii>; Fishery","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002703436,0.0001464589,0.0002119726,0.001057499,0.0006076304,0.0004309581,0.0002306951,0.0001386541,0.001070544],"category_scores_gemma":[0.001151015,0.0001848989,0.0002041414,0.0006077445,0.0006054586,0.0002767805,0.0005944587,0.00009843149,0.00006597389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317831,"about_ca_system_score_gemma":0.0008872548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2186682,"about_ca_topic_score_gemma":0.4026156,"domain_scores_codex":[0.9998351,0.00002723768,0.00000983547,0.00004207173,0.00004123477,0.00004436318],"domain_scores_gemma":[0.9993358,0.0001208046,0.0002260647,0.00003988677,0.0001687931,0.0001085932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000872215,0.000005081657,0.9877415,0.0000370462,0.00008822229,0.00004789692,0.0008864875,0.0005571712,0.007796051,0.0001224466,0.0000847308,0.002546056],"study_design_scores_gemma":[9.48367e-7,0.000006467797,0.9992024,0.000002363462,0.000006109314,0.00001774036,0.0002091339,0.0003953883,0.00007426184,0.00004365462,0.00003938334,0.000002060153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999625,0.00002317598,0.00008702451,0.000006178089,1.574071e-7,0.000001056497,0.00008757265,0.00000170189,0.0001682814],"genre_scores_gemma":[0.9997351,0.00001071391,0.00008302689,0.000002002068,2.412345e-7,0.000001795477,0.00008359265,6.882967e-7,0.00008279892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2186682,"threshold_uncertainty_score":0.4347908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01757397783503449,"score_gpt":0.1934921381529377,"score_spread":0.1759181603179032,"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."}}