{"id":"W1487237373","doi":"10.1111/caje.12201","title":"Reciprocal relationships and mechanism design","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Reciprocal; Collusion; Bayesian game; Mechanism (biology); Complete information; Set (abstract data type); Computer science; Mechanism design; Event (particle physics); Microeconomics; Sequential equilibrium; Bayesian probability; Principal (computer security); Mathematical economics; Repeated game; Economics; Game theory; Computer security; Artificial intelligence; Equilibrium selection","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.02502792,0.0009431964,0.001454427,0.001784543,0.001955736,0.006660686,0.002738239,0.004273909,0.009502079],"category_scores_gemma":[0.05030877,0.0009020727,0.001797385,0.001981643,0.008301351,0.009932995,0.004249019,0.003308518,0.001100844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003324829,"about_ca_system_score_gemma":0.002163988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005861989,"about_ca_topic_score_gemma":0.0003842747,"domain_scores_codex":[0.967606,0.02262499,0.001424517,0.003177101,0.003725522,0.001441821],"domain_scores_gemma":[0.9535654,0.0299934,0.006912902,0.006451352,0.002174269,0.0009028178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002485293,0.00003215374,0.0002111943,0.00005739671,0.00003038295,0.00004925984,0.0001562584,0.007583509,0.0001388013,0.9860473,0.0003332956,0.00533553],"study_design_scores_gemma":[0.00004826468,0.00003779216,0.0000834075,0.00003093421,0.00001563483,0.00008447362,0.00004546422,0.01972146,0.0001764454,0.976809,0.002935281,0.00001183177],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06719246,0.001660718,0.8453383,0.005004395,0.0001237119,0.0003855131,0.0001634406,0.0002230791,0.07990833],"genre_scores_gemma":[0.8659732,0.0008678038,0.1240182,0.0005209811,0.0001469408,0.0008493375,0.0001137378,0.00005175007,0.007457997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02502792,"threshold_uncertainty_score":0.1323618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4362847876896805,"score_gpt":0.250914882116373,"score_spread":0.1853699055733075,"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."}}