{"id":"W2159720663","doi":"10.1111/jbi.12479","title":"Stacked species distribution models and macroecological models provide congruent projections of avian species richness under climate change","year":2015,"lang":"en","type":"article","venue":"Journal of Biogeography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Fish and Wildlife Service","keywords":"Species richness; Body size and species richness; Ecology; Breeding bird survey; Climate change; Macroecology; Geography; Species distribution; Distribution (mathematics); Biodiversity; Biogeography; Abundance (ecology); Biology; Habitat","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004954644,0.0001874665,0.0003347714,0.0001347355,0.0001406443,0.00006822213,0.0002035743,0.0001099013,0.001150141],"category_scores_gemma":[0.00002577269,0.0001433936,0.0001960975,0.0005883581,0.0006071652,0.0007086931,0.000185755,0.0001662886,0.00001313196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000299815,"about_ca_system_score_gemma":0.00001859756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001102683,"about_ca_topic_score_gemma":0.0001447379,"domain_scores_codex":[0.9982888,0.00007952371,0.0005240978,0.0002053846,0.0005535282,0.0003486731],"domain_scores_gemma":[0.9989238,0.00003301617,0.0004759649,0.0001518474,0.0001587367,0.0002566298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009336717,0.002255963,0.9113016,0.0001324731,0.0002549148,0.0000641909,0.003241296,0.001704168,0.00565594,0.06281002,0.01033679,0.001308959],"study_design_scores_gemma":[0.001940819,0.001058789,0.9535782,0.000070042,0.0001581324,0.0001243358,0.01821268,0.001298921,0.001516332,0.01204739,0.009555453,0.0004388727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903563,0.000382945,0.001710588,0.001025072,0.0002765396,0.0003600436,0.0007189647,0.0000254524,0.005144066],"genre_scores_gemma":[0.9982053,0.001341823,0.0001499235,0.0001073829,0.00006619885,0.00001682374,0.00006517731,0.000008771419,0.00003856928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05076263,"threshold_uncertainty_score":0.999763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09151292649930459,"score_gpt":0.2702638054900988,"score_spread":0.1787508789907942,"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."}}