{"id":"W2777241338","doi":"10.3178/hrl.11.194","title":"Water pricing conflict in British Columbia","year":2017,"lang":"en","type":"article","venue":"Hydrological Research Letters","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation; Balsillie School of International Affairs; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Government (linguistics); Conflict resolution; Sustainability; Order (exchange); Conflict analysis; Commodification; Political science; Business; Environmental economics; Economics; Law; Economy; Finance","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001286978,0.0002323044,0.0006850783,0.001896714,0.009441417,0.007298348,0.001892246,0.002047076,0.008739024],"category_scores_gemma":[0.00834878,0.0003357402,0.0002887231,0.005694591,0.003489002,0.001485913,0.001761851,0.00231647,0.0004553608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08206364,"about_ca_system_score_gemma":0.03902358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9826466,"about_ca_topic_score_gemma":0.9919019,"domain_scores_codex":[0.9972252,0.0006969993,0.00009046293,0.0001892415,0.0007190113,0.001079148],"domain_scores_gemma":[0.9953206,0.0017068,0.0003719899,0.0001568571,0.0014536,0.0009901762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001685435,0.001246362,0.2097181,0.000730549,0.0006941019,0.01796159,0.03545769,0.06500418,0.003228596,0.3226143,0.1337398,0.2079194],"study_design_scores_gemma":[0.0004235291,0.0002774256,0.3673882,0.0007167555,0.0003875981,0.001708973,0.2032735,0.1165346,0.001592872,0.08300056,0.2237622,0.0009338898],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8797691,0.001393007,0.0006568364,0.006273987,0.00007853242,0.00009634141,0.0004259093,0.00003402976,0.1112722],"genre_scores_gemma":[0.9877146,0.0005890085,0.0003557811,0.0005918253,0.000006875117,0.00002759765,0.0001542456,0.00001241878,0.01054756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08206364,"threshold_uncertainty_score":0.5954162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3119408241995651,"score_gpt":0.4695521548736853,"score_spread":0.1576113306741202,"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."}}