{"id":"W43072628","doi":"10.1016/j.geb.2017.10.028","title":"On the optimality of diverse expert panels in persuasion games","year":2017,"lang":"en","type":"article","venue":"Games and Economic Behavior","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Persuasion; Undo; Diversity (politics); Intuition; Parameterized complexity; Heuristics; Action (physics); Computer science; Microeconomics; Mathematical economics; Psychology; Social psychology; Economics; Political science; Law","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":[],"category_scores_codex":[0.001019836,0.00007683929,0.0001731655,0.00004571347,0.0002194065,0.0001434813,0.0005597283,0.0000420881,0.000939039],"category_scores_gemma":[0.0001577738,0.00004740219,0.00006344639,0.00001794606,0.0002930319,0.000166902,0.0001633189,0.00006898723,0.0001319008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001675863,"about_ca_system_score_gemma":0.00001610531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002596668,"about_ca_topic_score_gemma":0.00005440109,"domain_scores_codex":[0.9992216,0.0000519753,0.0002699145,0.0002593065,0.00008584119,0.0001114129],"domain_scores_gemma":[0.9986157,0.0003426805,0.0002082641,0.0007741284,0.00001618287,0.00004307212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000191573,0.0004461556,0.3307557,0.000004012547,0.00001460703,0.000006883039,0.008694733,0.0001441844,0.004486651,0.1448353,0.00342855,0.5069916],"study_design_scores_gemma":[0.0003160205,0.00004678598,0.976288,0.00001295605,0.000008770888,0.000002698154,0.005182296,0.000289467,0.001714747,0.01352948,0.00250144,0.0001073202],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962417,0.00002634145,0.00001281541,0.001199858,0.00009966798,0.0001571339,0.00003049924,0.000004492821,0.002227503],"genre_scores_gemma":[0.9990284,0.00004575162,0.00004867648,0.00007018718,0.00002172221,0.00004359494,5.686325e-7,0.000003427711,0.0007376491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6455323,"threshold_uncertainty_score":0.9999743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2085810847554068,"score_gpt":0.4060143525765911,"score_spread":0.1974332678211843,"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."}}