{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002396072,0.0001184843,0.0001718576,0.0001467769,0.0001283885,0.0001647278,0.0006069416,0.00007854611,0.03028821],"category_scores_gemma":[0.001346123,0.00008947518,0.00007328467,0.0006302954,0.0002270468,0.0002809302,0.00009343837,0.0003476244,0.03798225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008706292,"about_ca_system_score_gemma":0.00002924078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001494777,"about_ca_topic_score_gemma":0.00002250047,"domain_scores_codex":[0.9983993,0.0001314839,0.0003378819,0.0004390405,0.0004830171,0.0002093177],"domain_scores_gemma":[0.9983155,0.0003620591,0.0001123079,0.0008862769,0.0002219205,0.0001019126],"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":[0.00002867646,0.000058228,0.0000649698,5.773795e-7,0.000004908704,0.000001645891,0.0001880493,0.000009543925,0.02210719,0.2976605,0.3903854,0.2894903],"study_design_scores_gemma":[0.0001125584,0.00001859402,0.002008612,4.472874e-7,0.000005422287,0.00001675517,0.00004165295,0.0001009617,0.002019839,0.3625607,0.6330422,0.00007224706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3434782,0.00004978009,0.05196949,0.1629797,0.01484601,0.001082281,0.00008561218,0.0004720149,0.425037],"genre_scores_gemma":[0.8087719,0.000005554906,0.002364969,0.001613835,0.05096562,0.0000416605,0.0000195487,0.00002433079,0.1361926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4652937,"threshold_uncertainty_score":0.9705982,"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."}}