{"id":"W2777060404","doi":"10.1109/spawc.2017.8227713","title":"Multiple access computational offloading with computation constraints","year":2017,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Computational resource; Computational complexity theory; Mobile cloud computing; Cloud computing; Distributed computing; Latency (audio); Mobile device; Resource allocation; Wireless; Computation; Efficient energy use; Mobile computing; Computer network; Algorithm; Telecommunications","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002045094,0.0001354932,0.0001425253,0.0000819205,0.0009625653,0.001645223,0.001128915,0.00003807036,0.000006008129],"category_scores_gemma":[0.00005529359,0.0001129827,0.00003555563,0.00008998215,0.0001719296,0.001485619,0.0004842114,0.0001060146,0.00005803754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003025952,"about_ca_system_score_gemma":0.00009785608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005908672,"about_ca_topic_score_gemma":0.000007073488,"domain_scores_codex":[0.9988901,0.00002557903,0.0001826629,0.0003522779,0.0002771195,0.0002722389],"domain_scores_gemma":[0.9989961,0.0001743092,0.000199295,0.0003681397,0.0001680896,0.00009406424],"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":[0.00003449105,0.0002023401,0.2254429,0.00005577975,0.0001330785,0.0001348675,0.001430164,0.0429661,0.0001986927,0.03670932,0.0176426,0.6750497],"study_design_scores_gemma":[0.0007617922,0.00003702225,0.1358632,0.00003915387,0.000003182006,0.00004505103,0.000008269819,0.857263,0.000282793,0.004865122,0.0006112135,0.0002202487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06365005,0.000003821614,0.9094436,0.0008868206,0.001970821,0.0001241682,2.176142e-7,0.0002144634,0.02370601],"genre_scores_gemma":[0.871904,2.389605e-7,0.1274862,0.0002289961,0.0002860222,0.000002733033,0.000003789473,0.000007086888,0.00008101851],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8142969,"threshold_uncertainty_score":0.9993911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0479887309494253,"score_gpt":0.3132189534970389,"score_spread":0.2652302225476136,"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."}}