{"id":"W3107537640","doi":"10.1145/3392142","title":"Mechanism Design for Online Resource Allocation","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Knapsack problem; Competitive analysis; Computer science; Valuation (finance); Payment; Incentive compatibility; Mechanism design; Resource allocation; Incentive; Function (biology); Resource (disambiguation); Allocative efficiency; Mathematical optimization; Operations research; Microeconomics; Business; 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":[],"consensus_categories":[],"category_scores_codex":[0.00182943,0.0001045231,0.0003277579,0.0001669106,0.0001136508,0.00009504476,0.001300578,0.00003433166,3.099964e-7],"category_scores_gemma":[0.0008973583,0.00007545416,0.0001346303,0.001060209,0.00002235014,0.00009314002,0.000303738,0.00006199633,1.687995e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002369962,"about_ca_system_score_gemma":0.0000236922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005179976,"about_ca_topic_score_gemma":2.446942e-7,"domain_scores_codex":[0.9984555,0.00003650706,0.0004193165,0.0002696954,0.0006849677,0.000134025],"domain_scores_gemma":[0.9983125,0.00009640091,0.0004819592,0.0002382324,0.0008080446,0.00006285329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001567285,0.0004737351,0.003378125,0.001752908,0.003616452,1.269857e-7,0.009158795,0.5121897,0.1944735,0.2598105,0.005181921,0.0098075],"study_design_scores_gemma":[0.000265042,0.0001594124,0.0003031489,0.0001315308,0.000191187,1.735337e-7,0.0001660575,0.989105,0.008937448,0.0005208398,0.0001391074,0.00008101481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03464177,0.000122726,0.9573528,0.00699141,0.00005564686,0.0006745356,0.000003084463,0.00006281302,0.00009518835],"genre_scores_gemma":[0.9461213,0.000006464378,0.05362034,0.0001911683,0.00003513832,0.000005244392,0.000001413594,0.000005873979,0.0000129993],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9114796,"threshold_uncertainty_score":0.3076932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1092157094810895,"score_gpt":0.2737351367538308,"score_spread":0.1645194272727413,"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."}}