{"id":"W1991469378","doi":"10.1287/mnsc.1040.0335","title":"Iterative Combinatorial Auctions with Bidder-Determined Combinations","year":2005,"lang":"en","type":"article","venue":"Management Science","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Bidding; Combinatorial auction; Common value auction; Computer science; Set (abstract data type); Vickrey–Clarke–Groves auction; Mathematical optimization; Resource allocation; Microeconomics; Auction theory; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001888266,0.0001234995,0.0001259753,0.0005707761,0.001460617,0.000588387,0.001149223,0.00002127137,0.0005162706],"category_scores_gemma":[0.0001721346,0.00008958227,0.00004282413,0.003586825,0.0009486774,0.001309785,0.0002236577,0.00009339346,0.001135665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008547227,"about_ca_system_score_gemma":0.00004490048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002568953,"about_ca_topic_score_gemma":0.00000880027,"domain_scores_codex":[0.9972854,0.00006764995,0.0003447814,0.000625941,0.001392664,0.0002835955],"domain_scores_gemma":[0.9984436,0.0001887097,0.0001709284,0.0007489694,0.0003112846,0.0001364838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001045126,0.0002186194,0.00030131,8.542185e-7,0.000007432949,0.000001541627,0.0003997558,0.001123797,0.0001282805,0.9708147,0.003018556,0.02397473],"study_design_scores_gemma":[0.00238737,0.0002554597,0.02432132,0.00002300507,0.00005229042,0.00002709029,0.004174122,0.01722497,0.003104116,0.4388109,0.509012,0.0006072922],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1867611,0.00001559399,0.324903,0.01742149,0.001552164,0.001380608,0.00002108064,0.0003807272,0.4675643],"genre_scores_gemma":[0.9792604,0.000002096643,0.004763376,0.0003082848,0.00009591949,0.0001060973,0.000001987283,0.000005768784,0.01545606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7924994,"threshold_uncertainty_score":0.9998394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04780430067086577,"score_gpt":0.3627959276296062,"score_spread":0.3149916269587404,"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."}}