{"id":"W2748683847","doi":"","title":"Toronto’s Private Tree By-Law: Performance Measurement Design and Cost-Benefit Analysis","year":2012,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Law; Computer science; Business; Political science","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":[0.0509432,0.0008603057,0.001135039,0.001793892,0.001084757,0.003262939,0.00146957,0.001335026,0.006786621],"category_scores_gemma":[0.07778305,0.0007307965,0.0008477737,0.002190283,0.002321012,0.001881726,0.001925263,0.001523203,0.0003190445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02934406,"about_ca_system_score_gemma":0.02513241,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1158233,"about_ca_topic_score_gemma":0.1189035,"domain_scores_codex":[0.9254909,0.06187758,0.001246146,0.002112275,0.00802403,0.001249088],"domain_scores_gemma":[0.935605,0.04857574,0.004065589,0.003701115,0.007177104,0.000875363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002429006,0.0006565824,0.0214602,0.001708167,0.0009669857,0.0002884024,0.002542476,0.2410784,0.003510347,0.3183081,0.01642805,0.3906233],"study_design_scores_gemma":[0.001800206,0.005486678,0.04180146,0.0009526124,0.001203651,0.0001291571,0.00177748,0.7480583,0.004192332,0.1267518,0.06757816,0.0002680895],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1013925,0.001417407,0.8322541,0.005497281,0.0002218328,0.0104929,0.001377919,0.000667233,0.04667879],"genre_scores_gemma":[0.675297,0.0005253808,0.3128117,0.0004771141,0.00006150067,0.005527148,0.0004044227,0.0001045868,0.004791094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8841767,"threshold_uncertainty_score":0.2694166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09570895494635775,"score_gpt":0.2666325077047995,"score_spread":0.1709235527584418,"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."}}