{"id":"W4214735731","doi":"10.1145/3410048.3410055","title":"Mechanism Design for Online Resource Allocation","year":2020,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"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); Mathematical optimization; Online algorithm; Allocative efficiency; 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":[0.004224562,0.0001561975,0.0002551396,0.0001903819,0.0001740253,0.0001018712,0.001269694,0.00005895583,0.00009468983],"category_scores_gemma":[0.006493183,0.0001430209,0.00008037289,0.00283284,0.00001393053,0.0006897845,0.0002123591,0.0001338789,0.0001070075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008301497,"about_ca_system_score_gemma":0.0002663156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.511307e-7,"about_ca_topic_score_gemma":1.206758e-7,"domain_scores_codex":[0.9975415,0.0003020372,0.0005154841,0.0004432151,0.0009454709,0.0002523075],"domain_scores_gemma":[0.9975438,0.0004030069,0.0002566223,0.0007035085,0.0009308106,0.0001623288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008394537,0.00007019065,0.00001444339,0.001156962,0.00001873975,2.01848e-7,0.0001865488,0.02238238,0.0001019955,0.007509655,0.01862681,0.9499237],"study_design_scores_gemma":[0.0004725594,0.00028751,0.00004832922,0.0002621084,0.00003930755,0.000001404756,0.000004247355,0.9409015,0.0004231361,0.0007084925,0.05667963,0.0001717596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001232449,0.01159011,0.9628781,0.02234304,0.00009920439,0.002658519,0.000003641293,0.0001461134,0.0001579965],"genre_scores_gemma":[0.01603811,0.06130182,0.8953099,0.02618344,0.0001604684,0.0006357277,0.0002205079,0.00002980978,0.0001202797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9497519,"threshold_uncertainty_score":0.7773416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2425125259377718,"score_gpt":0.3731375246778234,"score_spread":0.1306249987400516,"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."}}