{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01240256,0.00006186099,0.0002187423,0.000103735,0.001121273,0.003241169,0.002180219,0.00009542188,0.002598359],"category_scores_gemma":[0.007512346,0.00005628208,0.0000713015,0.0002004419,0.00116386,0.0002759592,0.0007271707,0.0006409356,0.001813307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003956099,"about_ca_system_score_gemma":0.00001631148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005171338,"about_ca_topic_score_gemma":0.008534233,"domain_scores_codex":[0.9962173,0.0007199471,0.0003690197,0.000605475,0.001337016,0.0007512385],"domain_scores_gemma":[0.9969097,0.001630445,0.0000611963,0.001092466,0.0001319619,0.0001742354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001027058,0.0004264076,0.5268946,0.00000848738,0.0000202383,0.0014943,0.00130617,0.0003557455,0.262652,0.001561908,0.1022794,0.102898],"study_design_scores_gemma":[0.0006573616,0.0001162083,0.7742609,0.00002276655,0.000001700334,0.00003018598,0.0001975074,0.000805845,0.00167541,0.1030801,0.1189359,0.0002161362],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670386,0.00001142318,0.000113263,0.02559346,0.00004446189,0.0002753412,0.00000405853,0.0000230021,0.006896399],"genre_scores_gemma":[0.9953541,0.0000101014,0.0000653214,0.001702993,0.00007610898,0.00008110872,0.000001933602,0.00000609692,0.002702309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2609766,"threshold_uncertainty_score":0.9989639,"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."}}