{"id":"W2785478723","doi":"10.1109/pimrc.2017.8292399","title":"The new enhancements in LTE-A Rel-13 for reliable machine type communications","year":2017,"lang":"en","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Machine to machine; Computer science; Wireless; Internet of Things; User equipment; Channel (broadcasting); The Internet; Computer network; Telecommunications; Embedded system; Base station","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":[0.006011805,0.001055531,0.0006733057,0.0009197662,0.0009778077,0.002088684,0.001297081,0.001863748,0.002627372],"category_scores_gemma":[0.004573906,0.0003921143,0.0009108928,0.0009060627,0.001184883,0.001140237,0.001162241,0.004086189,0.002133245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580809,"about_ca_system_score_gemma":0.00293133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00795934,"about_ca_topic_score_gemma":0.00789433,"domain_scores_codex":[0.9971473,0.0007286707,0.0003045095,0.0002298482,0.0009937896,0.0005959853],"domain_scores_gemma":[0.9939384,0.0009864032,0.0004574619,0.0009457243,0.003261254,0.0004107214],"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":[0.00227655,0.0005476145,0.01343266,0.001049266,0.0001712719,0.001430204,0.001654857,0.01744418,0.2038447,0.1567312,0.08181698,0.5196005],"study_design_scores_gemma":[0.0003438391,0.003420074,0.01391458,0.000584212,0.000312676,0.004312616,0.0005744804,0.05007022,0.05790416,0.02022237,0.8479764,0.0003643435],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08705936,0.01648375,0.7837111,0.009488087,0.006257902,0.001068462,0.001774812,0.006228133,0.08792837],"genre_scores_gemma":[0.6096705,0.008468861,0.3252831,0.01197983,0.002933603,0.001392674,0.004888176,0.0009676709,0.03441555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00795934,"threshold_uncertainty_score":0.03179383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03719275789090313,"score_gpt":0.3252317037271653,"score_spread":0.2880389458362622,"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."}}