{"id":"W2626118440","doi":"10.1016/j.mathsocsci.2021.01.002","title":"On the optimality of small research tournaments","year":2021,"lang":"en","type":"article","venue":"Mathematical Social Sciences","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Deutsche Forschungsgemeinschaft","keywords":"Tournament; Attractiveness; Mathematical optimization; Marginal cost; Mathematical economics; Computer science; Microeconomics; Economics; Econometrics; Mathematics; Combinatorics","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":["metaresearch","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01390095,0.00005058083,0.0001450849,0.00004985596,0.001320462,0.000218281,0.0008889144,0.0000395457,0.004046147],"category_scores_gemma":[0.00915704,0.00002567048,0.00009155169,0.001777722,0.001618,0.00006713938,0.000191675,0.0001573748,0.0005329439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000188737,"about_ca_system_score_gemma":0.0001047548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003834193,"about_ca_topic_score_gemma":0.000003494765,"domain_scores_codex":[0.9966595,0.000747591,0.0003672811,0.0002581524,0.001759302,0.0002082206],"domain_scores_gemma":[0.9925771,0.006657797,0.0001155501,0.0002546652,0.0003506681,0.00004421571],"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":[0.000002292377,0.0001104093,0.00005366188,0.000001429883,0.000002425717,4.226365e-7,0.0006424574,0.00001181339,0.0002586604,0.9942316,0.002313172,0.002371659],"study_design_scores_gemma":[0.00002949959,0.00002385896,0.0007582642,0.000007000346,0.000001700435,0.000001155108,0.004919763,0.0003421901,0.002363214,0.9900612,0.001459842,0.00003233076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7296604,0.00001240195,0.01200433,0.0223866,0.00006546147,0.0001485378,0.000006337101,0.00001240677,0.2357035],"genre_scores_gemma":[0.9959177,0.000001045568,0.001294129,0.0002385457,0.00005558702,0.00001750005,1.348879e-7,0.00000182626,0.002473508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2662573,"threshold_uncertainty_score":0.9999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.67073704658052,"score_gpt":0.5729856259180536,"score_spread":0.09775142066246645,"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."}}