{"id":"W2147242840","doi":"10.1109/icupc.1996.562721","title":"Improving the reliability of connections in cellular wireless environments via mobility tracking","year":2002,"lang":"en","type":"article","venue":"Proceedings of ICUPC - 5th International Conference on Universal Personal Communications","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Reliability (semiconductor); Computer network; Wireless; Track (disk drive); Tracking (education); Mobility model; Path (computing); Cellular radio; Mobile telephony; Mobile radio; Telecommunications; Base station","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003693809,0.001637232,0.00179408,0.001664774,0.00142449,0.001554404,0.002137845,0.001631979,0.001233615],"category_scores_gemma":[0.0274195,0.0006934819,0.0004920118,0.001580871,0.001006533,0.003557201,0.003084971,0.001896011,0.000777152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008964489,"about_ca_system_score_gemma":0.000825713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001562795,"about_ca_topic_score_gemma":0.001317521,"domain_scores_codex":[0.99765,0.0005973757,0.000150052,0.0003602027,0.0008960201,0.0003463054],"domain_scores_gemma":[0.9803122,0.0109112,0.001720184,0.003725173,0.003066337,0.0002648883],"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":[0.0008985279,0.000197326,0.007210586,0.0003601976,0.000188998,0.0004267808,0.000532265,0.5150968,0.07212432,0.01791318,0.003367289,0.3816837],"study_design_scores_gemma":[0.00005131886,0.0005785935,0.002678961,0.00006030727,0.000189574,0.0005906222,0.0001201994,0.9498222,0.0296018,0.01228644,0.003936943,0.00008307581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09506681,0.005649559,0.8935178,0.0005084955,0.0002359898,0.0001016487,0.0001274136,0.001690469,0.003101742],"genre_scores_gemma":[0.9271407,0.002332108,0.06842473,0.0001077643,0.0002466576,0.0000834465,0.0001787056,0.0001111174,0.001374759],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003693809,"threshold_uncertainty_score":0.01953495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05990576199373607,"score_gpt":0.2773139204472593,"score_spread":0.2174081584535232,"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."}}