{"id":"W2934866582","doi":"10.1109/access.2019.2907970","title":"Synchronization Procedure in 5G NR Systems","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Qatar National Research Fund; Fonds National de la Recherche Luxembourg; Qatar Foundation","keywords":"Synchronization (alternating current); Computer science; Frequency offset; Offset (computer science); Physical layer; Time synchronization; Data synchronization; Range (aeronautics); Frequency domain; Synchronization networks; Real-time computing; Electronic engineering; Telecommunications; Orthogonal frequency-division multiplexing; Wireless; Computer network; Wireless sensor network; Channel (broadcasting); Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005718278,0.00008323527,0.0001125203,0.0001001263,0.00001339315,0.00005292719,0.000407271,0.00006744761,0.00001604569],"category_scores_gemma":[0.000009018862,0.00008924171,0.00001139945,0.0002809249,0.000008108215,0.0005265427,0.0000232813,0.0001252212,0.00005598163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131289,"about_ca_system_score_gemma":0.00001131301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003160845,"about_ca_topic_score_gemma":0.00002431444,"domain_scores_codex":[0.9995124,0.00001464178,0.0001660228,0.0001006641,0.00008478989,0.0001214749],"domain_scores_gemma":[0.9995265,0.00002528957,0.00003096706,0.0003639205,0.0000342039,0.00001911087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004239759,0.00002795807,0.03125869,0.0006679299,0.00001167829,0.000001535067,0.0001977516,0.9466865,0.009907932,0.001448478,0.001390783,0.008396509],"study_design_scores_gemma":[0.0005673469,0.00002680444,0.01329475,0.0006792857,0.000005833346,0.000009460327,0.00009825435,0.8844,0.09307665,0.0008895807,0.006322571,0.0006294398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8364788,0.001415425,0.1452438,0.00004277117,0.000708561,0.0009723553,0.000004506461,0.001687553,0.0134462],"genre_scores_gemma":[0.99927,0.0002026697,0.0002460138,0.00001756692,0.00003023936,0.00009801664,0.000007462765,0.000031563,0.00009648194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1627912,"threshold_uncertainty_score":0.3639171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216147861588687,"score_gpt":0.2712158482827379,"score_spread":0.259054369666851,"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."}}