{"id":"W5517251","doi":"10.1007/bfb0040248","title":"A game programming approach to efficient management of interconnected power networks","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in control and information sciences","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Bargaining problem; Payment; Computer science; Game theory; Bargaining power; Mathematical optimization; Power (physics); Operations research; Nash equilibrium; Mathematical economics; Microeconomics; Economics; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.002527782,0.0002462549,0.0004441368,0.0007312617,0.0001389057,0.0003635143,0.0007063558,0.0001780551,0.00004791535],"category_scores_gemma":[0.0002136554,0.0001677177,0.0001011139,0.0006314152,0.0004029409,0.0004237415,0.0001450723,0.0002229961,0.00003314461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002928272,"about_ca_system_score_gemma":0.00003299533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001219806,"about_ca_topic_score_gemma":0.00000779147,"domain_scores_codex":[0.997281,0.00004663417,0.001081535,0.0003867685,0.000931714,0.0002723752],"domain_scores_gemma":[0.9980186,0.0007454628,0.0005601088,0.0003487809,0.0002465344,0.0000805727],"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":[0.00006504269,0.0000394991,0.00006243005,0.00003340459,0.00002436772,5.54636e-7,0.001144097,0.3831478,0.000004379447,0.2733501,0.0001049162,0.3420234],"study_design_scores_gemma":[0.002623142,0.000646651,0.003259282,0.0008792434,0.0001171039,0.00002990549,0.0007912777,0.5185743,0.0000492205,0.2137707,0.2578528,0.001406318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001175321,0.0002169982,0.7412944,0.0003229097,0.0001105327,0.0009066421,0.00002138374,0.00002640627,0.2559254],"genre_scores_gemma":[0.9954296,0.00001059716,0.003117338,0.0005743395,0.00002684504,0.00005820458,0.00001365758,0.000005598312,0.0007638241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9942543,"threshold_uncertainty_score":0.6839329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02494513286038843,"score_gpt":0.2889736009695584,"score_spread":0.26402846810917,"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."}}