{"id":"W3196174352","doi":"10.1111/gcb.15800","title":"Wealth and urbanization shape medium and large terrestrial mammal communities","year":2021,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas; University of Alberta","funders":"","keywords":"Urbanization; Species richness; Biodiversity; Per capita; Urban ecosystem; Ecology; Ecosystem; Geography; Ecosystem services; Mammal; Wildlife; Economic geography; Biology; Demography; Sociology; Population","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":[0.0003278864,0.0001371392,0.000192787,0.0009416972,0.0004577119,0.0008965053,0.0001995338,0.0002209965,0.003370559],"category_scores_gemma":[0.001643058,0.0001741208,0.0002138325,0.0007326346,0.0008160733,0.0007295443,0.001045727,0.0002394719,0.0002855035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002916802,"about_ca_system_score_gemma":0.000193789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01043154,"about_ca_topic_score_gemma":0.03673213,"domain_scores_codex":[0.9997154,0.0001116753,0.00001004581,0.00007484486,0.00003068658,0.00005747444],"domain_scores_gemma":[0.9991702,0.000194061,0.0003143871,0.00006731373,0.00008285622,0.0001712091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000792725,0.00003361411,0.9876846,0.00002210897,0.00008284553,0.0000955179,0.001595032,0.0003085909,0.001178309,0.0006217099,0.0004180484,0.00788019],"study_design_scores_gemma":[0.000001810297,0.00001229478,0.9974434,0.000007234377,0.00001147163,0.00003389474,0.00121435,0.0002873169,0.00004597027,0.0003460434,0.0005925469,0.000003652266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977888,0.0001613338,0.0001543414,0.00008715675,0.000002855817,0.000003303095,0.0001014836,0.000004273202,0.001696402],"genre_scores_gemma":[0.9995704,0.00006404098,0.00009956751,0.00002956003,0.00000268288,0.000002595224,0.000062821,0.000002848559,0.0001654428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01043154,"threshold_uncertainty_score":0.02074164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04527284936402489,"score_gpt":0.2871425242079984,"score_spread":0.2418696748439735,"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."}}