{"id":"W2618757379","doi":"","title":"Multi-Party Monitoring in Ontario: Challenges and Emerging Solutions","year":2011,"lang":"en","type":"article","venue":"","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Government (linguistics); Corporate governance; Context (archaeology); Public relations; Public engagement; Standardization; Political science; Process (computing); Business; Environmental resource management; Environmental planning; Geography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01285562,0.0005594171,0.0006650162,0.001651535,0.01209476,0.008092145,0.00412708,0.003358434,0.005258901],"category_scores_gemma":[0.01647757,0.0007907072,0.0006721488,0.006496589,0.006028223,0.005444617,0.006746712,0.002606948,0.0005276009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1183408,"about_ca_system_score_gemma":0.199091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9706783,"about_ca_topic_score_gemma":0.9792789,"domain_scores_codex":[0.9788933,0.003451356,0.0008892593,0.002143493,0.01057601,0.004046624],"domain_scores_gemma":[0.9634889,0.008556695,0.004290947,0.002507664,0.01514132,0.006014536],"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":[0.0003843885,0.000260938,0.1587716,0.003904591,0.0002241786,0.005351509,0.08291075,0.007102263,0.006766016,0.108954,0.198504,0.4268658],"study_design_scores_gemma":[0.00005608913,0.0001025614,0.1273465,0.001173498,0.00006578142,0.0006392762,0.05280959,0.007745721,0.001675261,0.02546826,0.7826816,0.0002358461],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2129636,0.02862128,0.03664299,0.5442313,0.001461579,0.001179408,0.003430568,0.001210884,0.1702585],"genre_scores_gemma":[0.8374386,0.01949508,0.04560651,0.0219596,0.0005390773,0.0005879932,0.002310036,0.0003374081,0.07172556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1183408,"threshold_uncertainty_score":0.8586267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030303735848203,"score_gpt":0.2849101548481736,"score_spread":0.1818797812633532,"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."}}