{"id":"W1539532232","doi":"10.1609/aimag.v31i4.2310","title":"Algorithmic Game Theory: Special Issue Introduction","year":2010,"lang":"en","type":"article","venue":"AI Magazine","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Game theory; Computer science; Algorithmic game theory; Mechanism (biology); Game design; Implementation theory; Management science; Artificial intelligence; Term (time); Data science; Repeated game; Mathematical economics; Engineering; Epistemology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001231461,0.001327515,0.001053867,0.002627345,0.0008709859,0.003650318,0.001183952,0.002460103,0.03109932],"category_scores_gemma":[0.003666657,0.0006171371,0.001173931,0.002945962,0.001794059,0.00524215,0.001388026,0.005014655,0.009358326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001457008,"about_ca_system_score_gemma":0.0009869321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007842227,"about_ca_topic_score_gemma":0.0008271707,"domain_scores_codex":[0.9991775,0.0001784026,0.00007962476,0.0001853032,0.0003143009,0.0000648021],"domain_scores_gemma":[0.9981254,0.001036778,0.00006418105,0.0001381389,0.0005034658,0.0001321088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003092096,0.0001079243,0.0004964226,0.001233322,0.00004353108,0.0001734842,0.0002881173,0.001436368,0.0006782245,0.2995479,0.5187857,0.1771781],"study_design_scores_gemma":[0.0000077443,0.00003650595,0.0003795253,0.0003423474,0.00001226355,0.0004447759,0.00007472412,0.0009606724,0.0001119016,0.1205041,0.8771082,0.00001718997],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"editorial","genre_scores_codex":[0.002937296,0.3865868,0.1220907,0.03342724,0.1105859,0.0002965735,0.001505726,0.0007448405,0.341825],"genre_scores_gemma":[0.05807333,0.4080661,0.07259177,0.02449051,0.187529,0.0007277186,0.003494492,0.001130736,0.2438963],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.03109932,"threshold_uncertainty_score":0.1040376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227147478713124,"score_gpt":0.3439779708345707,"score_spread":0.3212632229632583,"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."}}