{"id":"W2157112852","doi":"10.1109/icc.2007.62","title":"Modeling Channel Occupancy Times for Voice Traffic in Cellular Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Occupancy; Log-normal distribution; Channel (broadcasting); Exponential distribution; Computer science; Cellular network; Exponential function; Cellular traffic; Topology (electrical circuits); Computer network; Mathematics; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001372228,0.0006539888,0.0004846772,0.0007471852,0.0006291281,0.000960168,0.001004525,0.0009106407,0.0007743919],"category_scores_gemma":[0.007369215,0.0003849631,0.0004815386,0.0009564032,0.0008013445,0.001664742,0.000547082,0.0007655366,0.0002139506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002121038,"about_ca_system_score_gemma":0.0008981319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01744461,"about_ca_topic_score_gemma":0.0120721,"domain_scores_codex":[0.9992786,0.000206754,0.00003378812,0.000139133,0.000132843,0.0002088429],"domain_scores_gemma":[0.9959913,0.002825704,0.0004292904,0.0002699094,0.0003743284,0.0001094761],"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":[0.00005563343,0.00002856018,0.003826406,0.00001478789,0.000009916602,0.00005106755,0.0000921207,0.9851324,0.0007308552,0.005089522,0.0001895319,0.004779167],"study_design_scores_gemma":[0.000001708283,0.000009056126,0.0006183149,0.000001992463,0.000003441086,0.00002490695,0.00002536762,0.997613,0.00021225,0.001382388,0.0001030364,0.000004524158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5821841,0.0006073593,0.4134158,0.00023726,0.00003711642,0.00007315104,0.0003188936,0.0003186862,0.002807594],"genre_scores_gemma":[0.9889227,0.0002004078,0.009772545,0.00002141932,0.0000135647,0.00004448005,0.0001258263,0.00002684178,0.0008721441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01744461,"threshold_uncertainty_score":0.03468615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04000134872170089,"score_gpt":0.3028449741741415,"score_spread":0.2628436254524406,"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."}}