{"id":"W2017701133","doi":"10.1016/j.jeconom.2013.04.005","title":"What model for entry in first-price auctions? A nonparametric approach","year":2013,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; Center for Interuniversity Research and Analysis on Organizations; University of British Columbia","funders":"","keywords":"Common value auction; Nonparametric statistics; Econometrics; Selection (genetic algorithm); Model selection; Economics; Mathematical economics; Computer science; Mathematics; Microeconomics; Statistics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01416984,0.001595653,0.005273126,0.001907455,0.001428997,0.007611118,0.007582249,0.006625067,0.01092806],"category_scores_gemma":[0.06303548,0.001595848,0.004137521,0.002075684,0.003466797,0.01439458,0.0020549,0.006401276,0.002255413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001776994,"about_ca_system_score_gemma":0.002176387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006544447,"about_ca_topic_score_gemma":0.004261734,"domain_scores_codex":[0.9934336,0.004170985,0.0002660037,0.001004655,0.0004239995,0.0007007567],"domain_scores_gemma":[0.9495448,0.04009363,0.004201401,0.00330592,0.001722539,0.00113169],"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":[0.0003455024,0.0005600263,0.005896468,0.0004738471,0.0003908214,0.0004087224,0.0005267723,0.3860096,0.0006627342,0.5676796,0.010656,0.02638986],"study_design_scores_gemma":[0.00007299713,0.00005592028,0.0007418945,0.00004071384,0.00005688373,0.0001320717,0.0001215229,0.7540609,0.00008161782,0.2437495,0.0008342582,0.00005173848],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09349006,0.0007492615,0.889539,0.006063039,0.0001934991,0.0001996154,0.0008112349,0.0005553016,0.008399034],"genre_scores_gemma":[0.9092178,0.001117722,0.07079808,0.00075323,0.0005564722,0.0003943394,0.0009344572,0.0003370411,0.0158909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01416984,"threshold_uncertainty_score":0.07493818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3123202091683562,"score_gpt":0.354243343656133,"score_spread":0.04192313448777679,"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."}}