{"id":"W2931375168","doi":"10.3390/w11040663","title":"Governance Arrangements for Integrated Water Resources Management in Ontario, Canada, and Oregon, USA: Evolution and Lessons","year":2019,"lang":"en","type":"article","venue":"Water","topic":"Water resources management and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University","funders":"Oregon Watershed Enhancement Board","keywords":"Integrated water resources management; Corporate governance; Scope (computer science); Context (archaeology); Political science; Reflexivity; Scale (ratio); Mistake; Environmental resource management; Public administration; Environmental planning; Business; Water resources; Sociology; Geography; Economics; Ecology; Social science; Law","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":[0.002921653,0.0002088016,0.0002092016,0.001920378,0.006502594,0.006403187,0.001728867,0.0006198582,0.002488295],"category_scores_gemma":[0.005475223,0.0003519392,0.0002718349,0.004411147,0.005113787,0.001732248,0.002822601,0.0009161757,0.000116955],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.141317,"about_ca_system_score_gemma":0.1719495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9887784,"about_ca_topic_score_gemma":0.9967607,"domain_scores_codex":[0.9970642,0.0002723279,0.0001337098,0.0002687607,0.001496684,0.0007643367],"domain_scores_gemma":[0.992385,0.0006397885,0.0006219791,0.0004227062,0.004395214,0.001535218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000271651,0.0005379132,0.2775531,0.0006622247,0.0001857989,0.002459144,0.05807829,0.007045005,0.006024353,0.250602,0.05067938,0.3459012],"study_design_scores_gemma":[0.00009882437,0.0001559027,0.5070909,0.0005696587,0.0001000108,0.00038398,0.08666199,0.003736585,0.002197502,0.01044046,0.3883654,0.0001987684],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7630097,0.003619707,0.006473544,0.03060635,0.0001833772,0.001047991,0.001067566,0.00022775,0.193764],"genre_scores_gemma":[0.9517964,0.003257281,0.007872609,0.0008676329,0.00002027926,0.0001606201,0.0005531772,0.00004953238,0.03542242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.141317,"threshold_uncertainty_score":0.9959506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006047679040430998,"score_gpt":0.1671067887258311,"score_spread":0.1610591096854001,"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."}}