{"id":"W3197535271","doi":"10.1109/blackseacom52164.2021.9527781","title":"On Delay Sensitivity Clusters of Microgrid Data Aggregation Under LTE-A Links","year":2021,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Science Foundation","keywords":"Microgrid; Computer science; Latency (audio); Sensitivity (control systems); Overhead (engineering); Energy consumption; Smart grid; Low latency (capital markets); Computer network; Distributed computing; Real-time computing; Telecommunications; Engineering; Electronic engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008065481,0.0005648028,0.0003384968,0.0006439583,0.0004505105,0.0005999889,0.0005256214,0.0003212576,0.0004359588],"category_scores_gemma":[0.003596696,0.0001807237,0.000347586,0.0006330241,0.0004811516,0.0007210517,0.0004509713,0.000455751,0.00005695086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001368698,"about_ca_system_score_gemma":0.0005417149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0165822,"about_ca_topic_score_gemma":0.008325532,"domain_scores_codex":[0.9995796,0.0001004405,0.00001657339,0.0001116856,0.00008927299,0.0001024869],"domain_scores_gemma":[0.9978477,0.001278872,0.0003578036,0.0001345232,0.0002829251,0.00009821749],"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":[0.00009338464,0.00001955523,0.004894916,0.00002269411,0.00002045414,0.0001041878,0.00005777668,0.9866396,0.002398718,0.002137909,0.0002096521,0.003401123],"study_design_scores_gemma":[8.208497e-7,0.00001297454,0.001424722,0.000001608351,0.000004055945,0.00001521035,0.00002235236,0.9973736,0.000602857,0.0004905926,0.00004862441,0.000002729606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.912837,0.0005323812,0.08327321,0.0002843534,0.00003648707,0.00003944527,0.0001963754,0.0001995925,0.00260125],"genre_scores_gemma":[0.9980718,0.00007214086,0.001512899,0.00001116157,0.000007796311,0.000004735367,0.00004773853,0.000007617947,0.0002639692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0165822,"threshold_uncertainty_score":0.03297132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865954408906547,"score_gpt":0.236072958219666,"score_spread":0.2174134141306006,"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."}}