{"id":"W2607306415","doi":"10.1007/978-3-319-53472-5_1","title":"Relay Technology for 5G Networks and IoT Applications","year":2017,"lang":"en","type":"book-chapter","venue":"Studies in big data","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Relay; Software deployment; 3rd Generation Partnership Project 2; Computer science; Broadband; Computer network; LTE Advanced; Cellular network; Telecommunications; General partnership; Internet of Things; Telecommunications link; Computer security; Business","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":[0.0003170511,0.0008183869,0.0004023335,0.0007741388,0.0003238731,0.001227414,0.0007625667,0.001371499,0.01495192],"category_scores_gemma":[0.000618693,0.0002628097,0.0003550817,0.001027138,0.0007539546,0.002778525,0.0007454182,0.001400542,0.005281605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006765202,"about_ca_system_score_gemma":0.0003416833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000382318,"about_ca_topic_score_gemma":0.0005139213,"domain_scores_codex":[0.9997974,0.00004375357,0.00001105938,0.00004429695,0.00008697372,0.00001642276],"domain_scores_gemma":[0.9998046,0.0001042658,0.0000113583,0.00003370717,0.00003817712,0.000008037771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003627588,0.00003122309,0.00007519346,0.000680319,0.00002331029,0.0001693128,0.0002636111,0.002842502,0.01294354,0.5911626,0.06320464,0.3285675],"study_design_scores_gemma":[0.000007786021,0.00009123775,0.0001705438,0.0002741648,0.00003592503,0.0007730896,0.00009546299,0.006188271,0.005997944,0.1538306,0.8325098,0.00002515236],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.009381345,0.2011538,0.340803,0.007152252,0.005716369,0.0001248479,0.0003494478,0.001142891,0.4341761],"genre_scores_gemma":[0.1484657,0.2452736,0.1123382,0.002491382,0.00620384,0.0001961392,0.0005483847,0.0004793488,0.4840035],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01495192,"threshold_uncertainty_score":0.05001915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3514277441720988,"score_gpt":0.4016067699823458,"score_spread":0.05017902581024697,"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."}}