{"id":"W3110974438","doi":"10.1145/3444692","title":"A Survey on Edge Performance Benchmarking","year":2021,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Research Foundation of Korea; Royal Society","keywords":"Benchmarking; Computer science; Software deployment; Benchmark (surveying); Orchestration; Leverage (statistics); Data science; Context (archaeology); The Internet; Edge computing; Resource (disambiguation); Enhanced Data Rates for GSM Evolution; Distributed computing; World Wide Web; Software engineering; Telecommunications; Artificial intelligence","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.01322923,0.001106775,0.002872954,0.000550381,0.0007825353,0.0009196722,0.005868719,0.0005182969,0.000006835287],"category_scores_gemma":[0.001623986,0.001033303,0.0007560826,0.00269785,0.0000736548,0.000261809,0.004960086,0.001572092,0.0004103664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937395,"about_ca_system_score_gemma":0.0008948001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001517948,"about_ca_topic_score_gemma":0.000009382507,"domain_scores_codex":[0.9882116,0.006156577,0.001442478,0.001988243,0.0008130394,0.001388054],"domain_scores_gemma":[0.9877322,0.007149839,0.0009285656,0.003574918,0.0003587558,0.0002556978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.38747e-7,0.00006114631,0.0005709496,0.001721556,0.0001049897,0.00005568382,0.0001026359,0.00002942518,1.602387e-8,0.00004072476,0.008919412,0.9883931],"study_design_scores_gemma":[0.0002219505,0.0001806972,0.01031299,0.02598111,0.00008104688,0.0001024414,0.000001141025,0.01713968,0.000001328461,0.00001736162,0.9441196,0.001840606],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000164387,0.9197704,0.04881605,0.00001586418,0.02919274,0.0004416273,0.00000412792,0.0005456352,0.001049123],"genre_scores_gemma":[0.000228125,0.9803261,0.01156471,0.0001469617,0.00679262,0.00001081505,0.0005037055,0.0001487416,0.0002782384],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9865525,"threshold_uncertainty_score":0.99951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161239236735101,"score_gpt":0.3416418763134337,"score_spread":0.2255179526399236,"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."}}