{"id":"W4412509094","doi":"10.1007/978-981-96-6462-7_18","title":"Edge Computing in Wireless Multimedia Communications: Empowering Low-Latency and High-Quality Services","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Wireless; Latency (audio); Multimedia; Low latency (capital markets); Computer network; Enhanced Data Rates for GSM Evolution; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001343323,0.0005939852,0.000251876,0.0006170148,0.0003932201,0.002146633,0.0005986711,0.0009662781,0.01334593],"category_scores_gemma":[0.0002271179,0.000198629,0.0001902812,0.001181696,0.0005093405,0.00303126,0.0006959567,0.001675058,0.005366716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004220703,"about_ca_system_score_gemma":0.0003836663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004599993,"about_ca_topic_score_gemma":0.001176201,"domain_scores_codex":[0.9999045,0.00001044496,0.000003318374,0.0000162654,0.00005288568,0.00001255769],"domain_scores_gemma":[0.9999111,0.00003945289,0.000005048006,0.000006960715,0.00002640979,0.00001099912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002991897,0.00007795437,0.0001058475,0.0004650713,0.00001092884,0.0001412994,0.0002900597,0.001086934,0.009219554,0.3973858,0.1835215,0.4076651],"study_design_scores_gemma":[0.000002553371,0.00002214339,0.0001388017,0.0002337632,0.000007570742,0.0003366113,0.00009941977,0.002279272,0.002564756,0.04799329,0.9463119,0.00001005118],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00416864,0.1736759,0.09195878,0.005218713,0.008317304,0.00007387495,0.0001941157,0.0005473946,0.7158453],"genre_scores_gemma":[0.03709394,0.1518372,0.04096127,0.003359041,0.00410615,0.00006738958,0.0002461781,0.0003065733,0.7620223],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01334593,"threshold_uncertainty_score":0.04464656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0316651648514058,"score_gpt":0.3214026882420563,"score_spread":0.2897375233906505,"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."}}