{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01106062,0.002164219,0.002945191,0.001448621,0.001094597,0.004456908,0.004705864,0.003766629,0.008476414],"category_scores_gemma":[0.02009818,0.001396804,0.001923562,0.002651615,0.002701499,0.00652244,0.002990381,0.004049574,0.001519644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003140562,"about_ca_system_score_gemma":0.003717586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009894331,"about_ca_topic_score_gemma":0.0008160461,"domain_scores_codex":[0.988536,0.006959621,0.0005561474,0.001483899,0.001639957,0.000824442],"domain_scores_gemma":[0.9873668,0.009246275,0.001073511,0.001188457,0.0007650314,0.0003599746],"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":[0.0001651973,0.0002209153,0.000262106,0.0006764961,0.0001713312,0.0001811543,0.000130903,0.252552,0.001724813,0.6928656,0.004399282,0.04665019],"study_design_scores_gemma":[0.0001576659,0.0001546204,0.00007779215,0.00008087506,0.00005702478,0.0001686018,0.00003925151,0.6014552,0.0008481334,0.3876946,0.00922719,0.00003904833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003217291,0.0009849321,0.9879878,0.0005246925,0.0001177609,0.0002396723,0.00008540743,0.0002199533,0.006622533],"genre_scores_gemma":[0.4860119,0.003038078,0.4954511,0.00104752,0.0005379821,0.002419777,0.0003261855,0.0001832303,0.01098412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01106062,"threshold_uncertainty_score":0.05849487,"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."}}