{"id":"W1981347891","doi":"10.1111/ecog.00860","title":"Partitioning the variation in African vertebrate distributions into environmental and spatial components – exploring the link between ecology and biogeography","year":2014,"lang":"en","type":"article","venue":"Ecography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Erasmus+; Vlaamse regering; KU Leuven; McGill University","keywords":"Ecology; Biological dispersal; Spatial ecology; Range (aeronautics); Macroecology; Spatial variability; Biogeography; Biodiversity; Spatial analysis; Variation (astronomy); Taxonomic rank; Species richness; Biology; Geography; Taxon; Population; Statistics","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":[0.0006009372,0.000149434,0.0001818178,0.00105212,0.0002930631,0.0003682387,0.0001632736,0.0001326663,0.0007388548],"category_scores_gemma":[0.00213253,0.000110511,0.0002314766,0.001222856,0.0007821628,0.000466508,0.0005329387,0.0001690208,0.00004271316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002366414,"about_ca_system_score_gemma":0.0001854051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004365792,"about_ca_topic_score_gemma":0.008965197,"domain_scores_codex":[0.9996212,0.0002448052,0.00001561734,0.0000637656,0.00002526527,0.00002937636],"domain_scores_gemma":[0.9989601,0.0006576594,0.0002069498,0.0001092062,0.00004063019,0.00002546373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009480857,0.00002195496,0.9384104,0.00007720698,0.0002394937,0.0001347378,0.001016948,0.007003801,0.01643415,0.002606429,0.00005456478,0.03390548],"study_design_scores_gemma":[0.000002275595,0.0000185603,0.9885889,0.000009689524,0.00002203892,0.0001019857,0.0003134319,0.008645374,0.0004955158,0.001558232,0.0002370628,0.000006782303],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979988,0.000159213,0.001582032,0.00001713079,3.913936e-7,0.0000016724,0.00002114354,0.000001792902,0.0002179517],"genre_scores_gemma":[0.9992909,0.00006344668,0.000603743,0.000002269384,9.588827e-7,9.826055e-7,0.00002285455,0.00000115659,0.00001352679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004365792,"threshold_uncertainty_score":0.008680761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203361873229152,"score_gpt":0.2034396763368904,"score_spread":0.1831034890139752,"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."}}