{"id":"W4213419599","doi":"10.1111/ele.13898","title":"AVONET: morphological, ecological and geographical data for all birds","year":2022,"lang":"en","type":"letter","venue":"Ecology Letters","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":1160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of British Columbia; Birds Canada; Royal Ontario Museum; University of Toronto","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Ecology; Range (aeronautics); Trait; IUCN Red List; Biodiversity; Biology; Extant taxon; Evolutionary ecology; Taxonomic rank; Macroecology; Geography; Taxon; Evolutionary biology; Computer science","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":[0.005363059,0.0003925401,0.0005298496,0.001208771,0.0007401599,0.002583522,0.001751859,0.005146333,0.03983385],"category_scores_gemma":[0.03544028,0.0004192451,0.0004120747,0.001665003,0.001031421,0.002866022,0.002679116,0.004854742,0.04716329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239331,"about_ca_system_score_gemma":0.001668885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004994911,"about_ca_topic_score_gemma":0.00767594,"domain_scores_codex":[0.9966756,0.0009626611,0.000554235,0.0004685858,0.001126695,0.0002122001],"domain_scores_gemma":[0.9739763,0.01018469,0.001780509,0.005338394,0.006406031,0.002314109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006024724,0.000006191631,0.000934994,0.00005391239,0.000006541206,0.00008802446,0.00002363768,0.00002578877,0.0001081124,0.00141914,0.9803979,0.01687553],"study_design_scores_gemma":[0.00004047785,0.00001207155,0.002136532,0.0001590066,0.000003557354,0.0002329441,0.00003464543,0.0001328636,0.0001162806,0.003201839,0.993917,0.00001281925],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005015858,0.005146645,0.007124209,0.6487119,0.04679404,0.0003253715,0.2046105,0.001876534,0.08039486],"genre_scores_gemma":[0.03508307,0.006697249,0.01963982,0.4801711,0.03662513,0.001808049,0.2549363,0.002246312,0.1627929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03983385,"threshold_uncertainty_score":0.1332575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753539328103189,"score_gpt":0.2572490167350133,"score_spread":0.2297136234539814,"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."}}