{"id":"W2086158805","doi":"10.1016/j.psep.2012.05.001","title":"A rough set-based game theoretical approach for environmental decision-making: A case of offshore oil and gas operations","year":2012,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Minimax; Operations research; Interdependence; Stochastic game; Rough set; Computer science; Game theory; Set (abstract data type); Multiple-criteria decision analysis; Decision rule; Mathematical optimization; Management science; Data mining; Engineering; Mathematics; Artificial intelligence; Mathematical economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.003591266,0.0007617899,0.001156953,0.00139078,0.002183615,0.004682305,0.001944282,0.003737106,0.004936868],"category_scores_gemma":[0.006531723,0.0005286464,0.001567069,0.001069529,0.003338309,0.003040887,0.001631554,0.001950048,0.0002090393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004581795,"about_ca_system_score_gemma":0.003566288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01677645,"about_ca_topic_score_gemma":0.01518837,"domain_scores_codex":[0.9970548,0.002021272,0.00006612137,0.0001502299,0.0004131104,0.0002944272],"domain_scores_gemma":[0.9949007,0.004185208,0.0002094914,0.000132062,0.0002722856,0.0003002163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001840374,0.0002475644,0.0007552591,0.0001262302,0.00007607426,0.001836706,0.001305924,0.4381816,0.001046737,0.5488095,0.001149231,0.006281123],"study_design_scores_gemma":[0.0001280778,0.0001178713,0.0003812392,0.00003435101,0.00004931106,0.0001916183,0.001325706,0.8243973,0.0002676531,0.1707068,0.002339463,0.00006064085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3435155,0.0005534587,0.5440127,0.006774738,0.0001865184,0.0006054543,0.0002857019,0.0001252434,0.1039407],"genre_scores_gemma":[0.9537127,0.0001898001,0.04221275,0.000105767,0.00002070356,0.0001150516,0.00002827618,0.00001148671,0.003603482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01677645,"threshold_uncertainty_score":0.03335756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335531897439146,"score_gpt":0.2360885308627616,"score_spread":0.2227332118883702,"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."}}