{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007507742,0.0002881912,0.0002476089,0.00008475622,0.000357034,0.0001149423,0.0004330416,0.00009953643,0.0004994583],"category_scores_gemma":[0.000006129146,0.0003115275,0.00008995613,0.000319804,0.0001765126,0.002915423,0.0005587587,0.0001637684,0.0003116317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001110162,"about_ca_system_score_gemma":0.000003760196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009064063,"about_ca_topic_score_gemma":0.006053583,"domain_scores_codex":[0.9979551,0.0001634745,0.0002170721,0.0004693398,0.0006603451,0.0005346167],"domain_scores_gemma":[0.998993,0.00002788929,0.0001451372,0.0004405024,0.00001195063,0.0003815439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005036715,0.0001305862,0.9952028,0.0000108439,0.0001617592,0.000004604959,0.0001713966,0.0002522172,0.002166037,0.0000937192,0.000011978,0.001743689],"study_design_scores_gemma":[0.0006173873,0.00007845131,0.9571772,0.00001558149,0.0003690301,0.000002543004,0.00009182057,0.00001017297,0.003096929,0.00000806879,0.03816653,0.0003662643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887159,0.0001638558,0.007923978,0.0001474554,0.00007673728,0.0005118782,0.000006731641,0.00007706477,0.002376394],"genre_scores_gemma":[0.99406,0.0002336966,0.0003278638,0.001050017,0.00001567413,0.000006243336,0.00001613256,0.00002269642,0.004267671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03815455,"threshold_uncertainty_score":0.9999337,"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."}}