{"id":"W4252336338","doi":"10.1002/wcm.745","title":"Markov mobility model and registration area optimization in cellular networks","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada); Université de Moncton","funders":"","keywords":"Computer science; Markov chain; Cellular network; Mobility model; Cluster analysis; Markov model; Real-time computing; Computer network; Task (project management); Artificial intelligence; Machine learning","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":[0.001923832,0.0009877171,0.001328105,0.0007281764,0.0005426521,0.001010087,0.0012112,0.00102823,0.002212663],"category_scores_gemma":[0.005100433,0.0006089908,0.0007950284,0.001022806,0.001334228,0.001316208,0.00107621,0.001011369,0.0003535248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931926,"about_ca_system_score_gemma":0.0009109417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01031371,"about_ca_topic_score_gemma":0.00486415,"domain_scores_codex":[0.9987978,0.0005940578,0.00003590011,0.0001877658,0.0001693891,0.0002150283],"domain_scores_gemma":[0.9973266,0.001749043,0.0003667925,0.0001274719,0.0002949074,0.0001352605],"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":[0.00003002796,0.00000851699,0.0001914924,0.00000910786,0.000009070984,0.00001921469,0.00001274652,0.986173,0.0002180276,0.01113237,0.0002009618,0.001995542],"study_design_scores_gemma":[0.000004247228,0.00000850044,0.00003559476,0.000001155498,0.000002409901,0.00000430406,0.000003124082,0.9965799,0.00005052299,0.003219344,0.00008871146,0.00000211753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03943115,0.0003545647,0.9570286,0.0003412655,0.00003873543,0.00003828093,0.00007405392,0.0001458897,0.00254759],"genre_scores_gemma":[0.9497727,0.0004081975,0.04555761,0.00007419932,0.00004346617,0.0001099373,0.0001451272,0.00004264303,0.003846192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01031371,"threshold_uncertainty_score":0.0205074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771240212597911,"score_gpt":0.282081722646065,"score_spread":0.2543693205200859,"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."}}