{"id":"W4413125789","doi":"10.1109/tsc.2025.3596626","title":"Computing Offloading for Digital Twinning Empowered Industrial IoT","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Services Computing","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Internet of Things; Crystal twinning; Distributed computing; Computer network; Computer security","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":[0.0002564305,0.0004653998,0.0005898566,0.0003517181,0.0006477642,0.0009402416,0.0009586694,0.0004323126,0.00469734],"category_scores_gemma":[0.0005890856,0.0001538482,0.0003100915,0.0006200904,0.0004490457,0.001824221,0.001732971,0.0005861745,0.0005555408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004339526,"about_ca_system_score_gemma":0.0004953449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254329,"about_ca_topic_score_gemma":0.001636538,"domain_scores_codex":[0.9997093,0.00003668897,0.00001526381,0.00005713526,0.00007912725,0.0001024792],"domain_scores_gemma":[0.9997346,0.00006786251,0.00002145759,0.0000714745,0.00005414962,0.00005055865],"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":[0.0008431906,0.0004802051,0.003705408,0.0003344518,0.00006200862,0.00148993,0.0003482964,0.428362,0.05360177,0.1347692,0.01707161,0.358932],"study_design_scores_gemma":[0.00002231836,0.00009634369,0.0004369684,0.00001217631,0.00001393417,0.0001446457,0.00006357171,0.9662684,0.004920555,0.02030378,0.007700523,0.00001679633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1722297,0.001320316,0.7689996,0.0005856299,0.0004599016,0.0001593687,0.0001280873,0.002017948,0.05409952],"genre_scores_gemma":[0.9718325,0.0002099552,0.02424382,0.0001182113,0.00003786396,0.00004102833,0.00007688016,0.00005325338,0.003386538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00469734,"threshold_uncertainty_score":0.01571423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452910215755273,"score_gpt":0.2737835652834966,"score_spread":0.2492544631259439,"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."}}