{"id":"W4391014832","doi":"10.1002/9781394180523.ch8","title":"NOMA Empowered Multi‐Access Edge Computing and Edge Intelligence","year":2024,"lang":"en","type":"other","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Edge computing; Computer science; Noma; Computer network; 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":[0.000302268,0.000712593,0.000660259,0.0002363243,0.0004108068,0.001113013,0.0008039369,0.0004946188,0.002182174],"category_scores_gemma":[0.0006054112,0.0002488168,0.0004877081,0.0005261325,0.0003215043,0.0007387355,0.001106399,0.0008962093,0.0004566321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004208634,"about_ca_system_score_gemma":0.0008795103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002058248,"about_ca_topic_score_gemma":0.003924156,"domain_scores_codex":[0.9997242,0.00007136642,0.00001344831,0.00004394192,0.00007123716,0.0000757462],"domain_scores_gemma":[0.9997807,0.0001060217,0.00002461255,0.00002901442,0.0000383648,0.00002127255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001994907,0.0001405334,0.001068402,0.0004975991,0.00006684676,0.0005279788,0.0001550327,0.7187003,0.02123864,0.09027564,0.008815648,0.1583138],"study_design_scores_gemma":[0.000008098212,0.00003584173,0.0001242907,0.000009749917,0.000006945328,0.00005171615,0.0000323105,0.9881142,0.001070608,0.007370275,0.00316907,0.000006945811],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01961032,0.001306209,0.9655056,0.0002663358,0.0001699671,0.0001162729,0.0001040108,0.0002092945,0.01271202],"genre_scores_gemma":[0.7117017,0.002044168,0.2765043,0.0002396593,0.000165199,0.0002844491,0.0002304651,0.00005312722,0.008776904],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.002182174,"threshold_uncertainty_score":0.007300138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433609580789703,"score_gpt":0.330856120373929,"score_spread":0.2874951622949588,"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."}}