{"id":"W2102402730","doi":"10.1111/ecog.01128","title":"Greater consumption of protein‐poor anthropogenic food by urban relative to rural coyotes increases diet breadth and potential for human–wildlife conflict","year":2015,"lang":"en","type":"article","venue":"Ecography","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":154,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Directorate for Biological Sciences; Alberta Conservation Association","keywords":"Wildlife; Generalist and specialist species; Geography; Human–wildlife conflict; Ecology; Canis; Biology; Habitat","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":[0.000169309,0.0002143136,0.0001715185,0.0005346296,0.0005083273,0.0005727843,0.0002042199,0.0002141073,0.002142175],"category_scores_gemma":[0.000522366,0.0002190852,0.0001056335,0.0004418382,0.0006822349,0.0001424025,0.0004694113,0.0002461608,0.0001206057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002938913,"about_ca_system_score_gemma":0.0002759297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02694611,"about_ca_topic_score_gemma":0.1378291,"domain_scores_codex":[0.9998568,0.00002596684,0.000006777686,0.00003931247,0.00002952562,0.00004157494],"domain_scores_gemma":[0.9994831,0.00005746996,0.0002681286,0.00003026237,0.00004697268,0.0001141036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001550524,0.00005725555,0.985626,0.00002295699,0.00004675188,0.0001394533,0.0005144699,0.00005142075,0.01097431,0.00003987487,0.00008547372,0.002286974],"study_design_scores_gemma":[9.512607e-7,0.00001967012,0.9993355,0.000002230242,0.000004760011,0.00007431034,0.0003831841,0.00002642884,0.0000906324,0.000006647843,0.00005462303,9.466127e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997095,0.00002990751,0.00002133567,0.0000064224,3.813569e-7,0.000001160823,0.00001683188,7.802967e-7,0.0002137195],"genre_scores_gemma":[0.9995831,0.00004356704,0.00008929851,0.00001258007,0.000001341239,0.000002622547,0.00004742821,0.000001167841,0.0002190731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02694611,"threshold_uncertainty_score":0.0535785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02004374807370429,"score_gpt":0.2423492339989278,"score_spread":0.2223054859252235,"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."}}