{"id":"W2889125649","doi":"10.1109/ccece.2018.8447629","title":"A Performance Evaluation of Millimeter-Wave Cellular Networks with User Mobility","year":2018,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Blocking (statistics); Handover; Base station; Computer network; Cellular network; Extremely high frequency; Overhead (engineering); Mobility model; Stochastic geometry; Mobile telephony; Path loss; User equipment; Electronic engineering; Real-time computing; Telecommunications; Mobile radio; Engineering; Wireless; Mathematics","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":[0.001057134,0.0006178904,0.0004482396,0.0007029689,0.0004399725,0.0005859816,0.0004331589,0.0006887895,0.0005449927],"category_scores_gemma":[0.003901503,0.0001230864,0.0002455855,0.00111837,0.0004125719,0.0007300305,0.0005021565,0.0002863453,0.0001270033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000986332,"about_ca_system_score_gemma":0.0003544652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006476133,"about_ca_topic_score_gemma":0.002984723,"domain_scores_codex":[0.9989902,0.0003803823,0.00005436234,0.00009092854,0.0002356546,0.0002485077],"domain_scores_gemma":[0.9974763,0.001400133,0.0002754564,0.0002010086,0.0005565683,0.00009044593],"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":[0.001006866,0.0001620863,0.02203959,0.0001550081,0.0001286526,0.0004445202,0.0001524523,0.91284,0.02906233,0.002900433,0.00061477,0.03049328],"study_design_scores_gemma":[0.00001479078,0.000959742,0.01030872,0.00001415616,0.00007090073,0.0003391684,0.0001426725,0.9698009,0.01729511,0.000515332,0.0005114818,0.00002705746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848034,0.0007791843,0.01116479,0.0001658789,0.00002320139,0.00002304566,0.0001542225,0.00012483,0.002761344],"genre_scores_gemma":[0.9988142,0.000146708,0.0007723232,0.000009031362,0.00000555304,0.000006125863,0.0000578682,0.000003394865,0.0001848093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006476133,"threshold_uncertainty_score":0.01287687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03660980971512146,"score_gpt":0.2272461338466828,"score_spread":0.1906363241315613,"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."}}