{"id":"W4402386394","doi":"10.48550/arxiv.2408.05146","title":"Performative Prediction on Games and Mechanism Design","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Samsung; European Commission; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Performative utterance; Mechanism design; Mechanism (biology); Computer science; Human–computer interaction; Mathematical economics; Aesthetics; Art; Mathematics; Epistemology; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004276595,0.0002350909,0.0003366584,0.0004015693,0.0001288776,0.0001036442,0.0001965627,0.0002357485,0.0002328942],"category_scores_gemma":[0.0000143843,0.0002766801,0.0001204916,0.0001849819,0.00004659027,0.0001196157,0.00033963,0.0006430551,0.0004542175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001569476,"about_ca_system_score_gemma":0.00003390773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008895403,"about_ca_topic_score_gemma":0.00000430192,"domain_scores_codex":[0.9988059,0.00001416953,0.0002638037,0.0006945008,0.00001788275,0.0002036848],"domain_scores_gemma":[0.9992479,0.00003505965,0.0002348361,0.0003613674,0.00003021791,0.00009063734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003637087,0.00003627151,0.002453337,0.0001345552,0.0001504563,0.00004223939,0.0004814571,0.0828327,0.00000120378,0.9129558,0.0006986023,0.0001769651],"study_design_scores_gemma":[0.000166258,0.00009376917,0.001379374,0.00008903051,0.00003778618,0.000001880475,0.00009590452,0.6393608,0.00003514352,0.3573052,0.001195095,0.0002397572],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9085335,0.0007694022,0.0658127,0.0001488153,0.001359829,0.0004210962,0.0004070699,0.0001398049,0.02240778],"genre_scores_gemma":[0.9925549,0.002359457,0.00008965807,0.00007913291,0.0001011897,0.000001729932,0.00002126347,0.00002496558,0.004767728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5565281,"threshold_uncertainty_score":0.9999685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1080047993888678,"score_gpt":0.1632515457243222,"score_spread":0.05524674633545432,"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."}}