{"id":"W2016739114","doi":"10.1006/jema.2001.0557","title":"Groundwater management by watershed agencies: an evaluation of the capacity of Ontario’s conservation authorities","year":2002,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Local government; Business; Watershed management; Environmental planning; Environmental resource management; Groundwater; Watershed; Government (linguistics); Resource management (computing); CLARITY; Water resources; Public administration; Political science; Environmental science; Engineering","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":[0.009756371,0.0003282114,0.0003473781,0.002024914,0.00363072,0.00331516,0.001789451,0.00166979,0.003155138],"category_scores_gemma":[0.03913172,0.0003907331,0.0007205702,0.002719489,0.003082987,0.002897829,0.002393544,0.0008623818,0.0002393171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04891678,"about_ca_system_score_gemma":0.068939,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9339989,"about_ca_topic_score_gemma":0.9777579,"domain_scores_codex":[0.9879057,0.003124963,0.0004984079,0.0004463528,0.005640984,0.002383622],"domain_scores_gemma":[0.9486398,0.02102078,0.005681287,0.002143497,0.01589007,0.006624707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00211539,0.001055005,0.8854347,0.0002457887,0.000290922,0.000559367,0.008943114,0.01477103,0.001452829,0.009204692,0.008135355,0.06779187],"study_design_scores_gemma":[0.0004461239,0.001156531,0.9467337,0.0001583007,0.0002780413,0.0001227619,0.01688089,0.01129728,0.0008960215,0.001369177,0.0205638,0.00009735738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9655364,0.0001903224,0.0002412958,0.002697611,0.00001185454,0.0003205047,0.0005115864,0.00001877129,0.03047169],"genre_scores_gemma":[0.9965028,0.0001906365,0.000586525,0.0001473195,0.000009727416,0.00007008971,0.0002501573,0.000004503012,0.002238252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06600106,"threshold_uncertainty_score":0.3549177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798599061847445,"score_gpt":0.1990250431128313,"score_spread":0.1710390524943569,"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."}}