{"id":"W4385423553","doi":"10.1007/s11276-023-03456-9","title":"Adaptive computation offloading for latency-sensitive tasks in heterogeneous edge-cloud-enabled smart warehouses using Gau-Angle FIS and AGE-MOEA-II","year":2023,"lang":"en","type":"article","venue":"Wireless Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; Quanzhou City Science and Technology Program; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Latency (audio); Service (business); Profit (economics); Computation; Distributed computing; Algorithm; Operating system","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"],"consensus_categories":[],"category_scores_codex":[0.0005301345,0.0003048705,0.0004520124,0.0002813708,0.0006181281,0.0002197844,0.0003202607,0.0001884079,4.381344e-7],"category_scores_gemma":[0.00003368347,0.0003233239,0.0001026912,0.001016813,0.00007893595,0.0003197544,0.000563489,0.000264494,0.000006237688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001366205,"about_ca_system_score_gemma":0.00006906557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001687065,"about_ca_topic_score_gemma":0.00006979633,"domain_scores_codex":[0.9976891,0.0001466798,0.0004304243,0.000705023,0.0002048568,0.000823881],"domain_scores_gemma":[0.9987634,0.0005319615,0.000183861,0.0002523287,0.0001425182,0.0001259606],"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":[0.0001290568,0.0001123791,0.002467938,0.00009463426,0.0001362604,0.0006110166,0.01049519,0.8337158,0.0006542193,0.0004688882,0.00410653,0.1470081],"study_design_scores_gemma":[0.0006773213,0.0001384494,0.001858044,0.0002457746,0.00001613895,0.00004050645,0.00008678077,0.9953362,0.0003059079,0.0007309606,0.000185369,0.0003785501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.537688,0.0001310393,0.4581912,0.00008492687,0.003174108,0.000376402,0.000001235644,0.0002928634,0.00006022301],"genre_scores_gemma":[0.9899709,0.0000288993,0.008330361,0.0001615318,0.0013526,0.00002359081,0.00002626198,0.000046122,0.00005969207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4522829,"threshold_uncertainty_score":0.9999219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03727653571500918,"score_gpt":0.2620590315661266,"score_spread":0.2247824958511175,"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."}}