{"id":"W2294857041","doi":"","title":"Revenue-maximizing and truthful online auctions for dynamic spectrum access","year":2016,"lang":"en","type":"article","venue":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Auction algorithm; Combinatorial auction; Spectrum auction; Common value auction; Revenue; Revenue equivalence; Generalized second-price auction; Exploit; Scalability; Vickrey–Clarke–Groves auction; Mathematical optimization; Auction theory; Computer security; Microeconomics; Mathematics; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.00112637,0.0002026093,0.0003306441,0.001138245,0.0004709801,0.0001436896,0.001532268,0.0001956143,0.0002203764],"category_scores_gemma":[0.006230245,0.0001484744,0.00009572941,0.001746639,0.0008863074,0.001605807,0.0006002708,0.0001725846,0.00005852903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006781409,"about_ca_system_score_gemma":0.0001372641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000230729,"about_ca_topic_score_gemma":0.000136727,"domain_scores_codex":[0.9975732,0.00004309982,0.0008732508,0.0008058585,0.0003911319,0.0003134425],"domain_scores_gemma":[0.9965891,0.0003136044,0.0007274111,0.001609576,0.0006301027,0.0001302256],"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":[0.0001139153,0.000635858,0.003991554,0.00004856096,0.00009466694,0.000001853255,0.00004644286,0.0001614616,0.006006559,0.6617543,0.05144042,0.2757044],"study_design_scores_gemma":[0.001064911,0.00007663689,0.004849197,0.00008615914,0.00005795151,0.00002870772,0.0001794022,0.002220332,0.006015832,0.1389591,0.8461223,0.0003394468],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1367909,0.0001900899,0.7342322,0.1175,0.0007471911,0.001129407,0.008256879,0.0004487185,0.0007046375],"genre_scores_gemma":[0.9668152,0.0001651603,0.02559604,0.000245821,0.0001373041,0.0004381571,0.0006282375,0.00002776758,0.005946345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8300242,"threshold_uncertainty_score":0.7458636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08814194811173497,"score_gpt":0.3980292106730106,"score_spread":0.3098872625612756,"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."}}