{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004173031,0.0001545868,0.0003523405,0.0007023671,0.0003711174,0.0001666017,0.0005868679,0.0001515933,0.0006217237],"category_scores_gemma":[0.002639006,0.0001234216,0.0001129544,0.0001731899,0.0002381539,0.0006760457,0.00001906569,0.0002164854,0.0001351292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006186513,"about_ca_system_score_gemma":0.001305518,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003129837,"about_ca_topic_score_gemma":0.6234136,"domain_scores_codex":[0.9980834,0.000253444,0.0009386592,0.0003361282,0.000005066758,0.0003833485],"domain_scores_gemma":[0.9952745,0.001703112,0.0006649072,0.0004112921,0.0002856604,0.001660462],"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":[0.00002654747,0.000002771804,0.001503982,8.872697e-7,0.00002187635,0.00001316107,0.0003666075,0.0003053478,0.00005602433,0.9815902,0.0009747345,0.01513788],"study_design_scores_gemma":[0.0003099814,0.000112686,0.0009094254,0.0000242424,0.00001331564,0.0004958973,0.0005017317,0.0002973638,0.0003576131,0.9692657,0.02754216,0.0001698644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9355977,0.00006490704,0.05375429,0.00902707,0.0006277969,0.0001664507,0.00006588584,0.000005007832,0.0006909352],"genre_scores_gemma":[0.9945927,0.00004358699,0.002523644,0.0002848553,0.0003117676,0.00001191389,6.44152e-7,0.00001962966,0.002211252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6202838,"threshold_uncertainty_score":0.6807438,"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."}}