{"id":"W1553324755","doi":"","title":"ECONOMIC TOOLS FOR MANAGING IMPACTS OF URBAN CANADA GEESE","year":2000,"lang":"en","type":"article","venue":"Lincoln (University of Nebraska)","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Economic impact analysis; Lawn; Business; Environmental planning; Scale (ratio); Environmental resource management; Geography; Natural resource economics; Economics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003459246,0.00117159,0.0007264332,0.004914902,0.0007566279,0.00336319,0.001083165,0.0009672241,0.004080604],"category_scores_gemma":[0.009973155,0.0005344761,0.0006577646,0.00361185,0.001503528,0.003466291,0.001582512,0.001839215,0.0002685215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003615902,"about_ca_system_score_gemma":0.002973299,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02033461,"about_ca_topic_score_gemma":0.0203679,"domain_scores_codex":[0.9990113,0.000487898,0.00005253415,0.00004927165,0.0003265195,0.00007244397],"domain_scores_gemma":[0.9970562,0.002005702,0.0003341942,0.00010767,0.0004215808,0.00007455849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002346228,0.00007654469,0.001439002,0.0001175827,0.00005195767,0.0001293516,0.00007944555,0.5408146,0.0002000422,0.3912286,0.004115425,0.06172382],"study_design_scores_gemma":[0.0000262668,0.00003511597,0.001371228,0.0001268546,0.00003885927,0.00004829279,0.000243244,0.659503,0.0002318802,0.3222458,0.01608988,0.00003959329],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02999103,0.003481133,0.8963913,0.004299103,0.0001794476,0.000443348,0.0005080225,0.0003154701,0.06439118],"genre_scores_gemma":[0.6981617,0.008960947,0.2813984,0.0001955374,0.0003479633,0.0008574902,0.0004111718,0.0001084702,0.009558381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9796654,"threshold_uncertainty_score":0.04043245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03650636971865514,"score_gpt":0.1697404462650867,"score_spread":0.1332340765464315,"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."}}