{"id":"W1567501259","doi":"10.1007/978-3-540-70829-2_14","title":"Opposition Mining in Reservoir Management","year":2008,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Water resources management and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Opposition (politics); Curse of dimensionality; Computer science; Reinforcement learning; Operations research; Artificial intelligence; Water resources; Mathematical optimization; Engineering; Mathematics; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001141254,0.0002444169,0.0002570335,0.000531567,0.00004698304,0.00001840801,0.0001836088,0.00008344538,0.00003353973],"category_scores_gemma":[0.000006728099,0.0002784736,0.00004656891,0.0001139796,0.0000937876,0.00009053943,0.0001534773,0.0001880756,0.00006088029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002956718,"about_ca_system_score_gemma":0.000004311988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002163586,"about_ca_topic_score_gemma":0.00003437488,"domain_scores_codex":[0.998807,0.00001066952,0.0004613389,0.000267086,0.0002720953,0.0001817869],"domain_scores_gemma":[0.9996502,0.0000996529,0.00005602416,0.0001178769,0.00005638372,0.00001980957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007416857,0.000007256608,0.00003132789,0.0002370926,0.0001008785,0.0001452666,0.001301466,0.9800185,3.028785e-8,0.009378625,0.002538652,0.006233471],"study_design_scores_gemma":[0.0003200546,0.00006885227,0.0004118128,0.003093332,0.00004677307,0.00001458385,0.00100745,0.8695834,0.00001218147,0.08227879,0.04208107,0.001081728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0008594525,0.008553176,0.04920274,0.0001209428,0.0008598901,0.0007798071,0.00001162357,0.0002324341,0.9393799],"genre_scores_gemma":[0.5447682,0.09054583,0.09507697,0.0003816623,0.0007108207,0.0003616751,0.0009784533,0.000420683,0.2667557],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6726242,"threshold_uncertainty_score":0.9999667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08467941172914151,"score_gpt":0.2938382952940354,"score_spread":0.2091588835648939,"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."}}