{"id":"W2014398373","doi":"10.1007/s10994-006-0477-8","title":"Bidding agents for online auctions with hidden bids","year":2006,"lang":"en","type":"article","venue":"Machine Learning","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Common value auction; Bidding; Valuation (finance); Computer science; Combinatorial auction; Artificial intelligence; Machine learning; Ex-ante; Econometrics; Mathematical optimization; Microeconomics; Economics; Mathematics","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":[0.00736086,0.001112931,0.003139202,0.000798811,0.001261917,0.005869811,0.004087396,0.003129324,0.00856029],"category_scores_gemma":[0.03351939,0.001723197,0.001321297,0.001393181,0.002563059,0.01076215,0.002791017,0.004382628,0.001102451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442806,"about_ca_system_score_gemma":0.002319884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001483852,"about_ca_topic_score_gemma":0.001690154,"domain_scores_codex":[0.9963719,0.002222542,0.0002090698,0.0003771741,0.0005058232,0.0003135469],"domain_scores_gemma":[0.9783149,0.01708568,0.001279827,0.001567008,0.001064274,0.0006882808],"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":[0.0005187676,0.0002715803,0.0006894296,0.0002648371,0.0001068332,0.0002286819,0.0003559608,0.2286072,0.0006824628,0.7351155,0.004319889,0.02883881],"study_design_scores_gemma":[0.00007001768,0.00002249411,0.000061924,0.00001425112,0.00001463981,0.00003276016,0.00002678479,0.6239541,0.0001085889,0.3751383,0.0005426588,0.00001333773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04171797,0.0004310822,0.9501852,0.0009188503,0.0001168463,0.0001188502,0.0001185704,0.0001953718,0.006197164],"genre_scores_gemma":[0.7610824,0.0006761841,0.2177613,0.0002569657,0.0003008795,0.0004361061,0.000324903,0.0002249325,0.01893635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00856029,"threshold_uncertainty_score":0.03892839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.078163754291518,"score_gpt":0.388055020704645,"score_spread":0.309891266413127,"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."}}