{"id":"W2962229258","doi":"10.1109/icc.2019.8762083","title":"Protocol Stack Perspective for Low Latency and Massive Connectivity in Future Cellular Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Protocol stack; Low latency (capital markets); Latency (audio); Cellular network; Communications protocol; Protocol (science); Data transmission; Internet of Things; Edge computing; Enhanced Data Rates for GSM Evolution","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":[0.002164046,0.0009447865,0.0004894956,0.001242362,0.001521198,0.006240766,0.00165929,0.002375327,0.002827373],"category_scores_gemma":[0.002715721,0.000440056,0.0006093877,0.001259839,0.001976758,0.006935964,0.0018516,0.00442702,0.0009527879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764726,"about_ca_system_score_gemma":0.001843723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002079918,"about_ca_topic_score_gemma":0.001667484,"domain_scores_codex":[0.9988311,0.0003168066,0.0001005191,0.0001417656,0.0004153229,0.0001945044],"domain_scores_gemma":[0.9989728,0.0003238573,0.0001011427,0.0002098663,0.0003170604,0.00007539023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001057297,0.00001495122,0.00006457915,0.00008982855,0.000008009913,0.0001282047,0.0001175626,0.00316799,0.001426414,0.9824034,0.001935586,0.01063279],"study_design_scores_gemma":[0.00001508883,0.0001016506,0.0002245605,0.0003371831,0.00005074412,0.0005986884,0.0003889589,0.0691337,0.003859789,0.7611468,0.1640865,0.0000563891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01372615,0.01888997,0.8405586,0.01663073,0.003072075,0.0003597689,0.0002508425,0.0004366538,0.1060752],"genre_scores_gemma":[0.4841035,0.03561334,0.4301856,0.005475597,0.003867697,0.001866907,0.0006476553,0.0002337887,0.03800591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006240766,"threshold_uncertainty_score":0.01280409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005968801581561793,"score_gpt":0.2378120898663589,"score_spread":0.2318432882847971,"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."}}