{"id":"W2143988898","doi":"10.1145/511442.511445","title":"Estimation of blocking probabilities in cellular networks with dynamic channel assignment","year":2002,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Blocking (statistics); Computer science; Estimator; Channel (broadcasting); Importance sampling; Mathematical optimization; Call blocking; Algorithm; Mathematics; Statistics; Monte Carlo method; Telecommunications","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":[0.0001397236,0.000113778,0.0001404746,0.0002400924,0.0001154267,0.0000483422,0.00007125355,0.00004274341,0.000009364464],"category_scores_gemma":[0.000005235532,0.0001071713,0.00003217179,0.000240826,0.00002053269,0.0004511751,0.000006555375,0.00009846463,0.000001440317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002911835,"about_ca_system_score_gemma":0.000001579812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003194686,"about_ca_topic_score_gemma":0.00001910304,"domain_scores_codex":[0.999324,0.00001463936,0.0002231357,0.0002030744,0.000121435,0.0001137496],"domain_scores_gemma":[0.9995949,0.00007199879,0.00009049295,0.0001885072,0.00004790176,0.000006221201],"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":[0.00002656252,0.00006515672,0.00002165871,0.00003680793,0.00001457664,5.04034e-7,0.0001295134,0.9537821,0.000003627127,0.0001434823,8.672139e-8,0.04577597],"study_design_scores_gemma":[0.0003317356,0.00002332346,0.00001539013,0.0001248632,0.00004551523,2.689154e-7,0.00004741423,0.9916089,0.000007160119,0.007679944,0.000001392108,0.0001140854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2647268,0.0000261503,0.7349901,0.00006085425,0.00003457408,0.0001040381,2.382712e-7,0.00004289426,0.00001435989],"genre_scores_gemma":[0.9930681,0.000005902113,0.006789412,0.00005586671,0.00004080513,0.00001060253,0.000006412215,0.00001328781,0.000009632799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7283413,"threshold_uncertainty_score":0.4370319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01828721948131391,"score_gpt":0.2142329153664802,"score_spread":0.1959456958851663,"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."}}