{"id":"W1991996397","doi":"10.1109/icc.2014.6883675","title":"Joint access class barring and timing advance model for machine-type communications","year":2014,"lang":"en","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Random access; Computer science; Base station; Computer network; Wireless; Joint (building); LTE Advanced; Transmission (telecommunications); Cellular network; Telecommunications link; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001371868,0.00007352425,0.00009922637,0.00002358463,0.00006915441,0.00005792779,0.000200007,0.00003481611,0.000006153017],"category_scores_gemma":[0.00001930794,0.0000668237,0.00001918155,0.00004342605,0.0000113534,0.0001744315,0.00008604959,0.00008208567,0.000002502154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001364304,"about_ca_system_score_gemma":0.000004094346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003304525,"about_ca_topic_score_gemma":0.000041372,"domain_scores_codex":[0.9996472,0.000008044723,0.000123387,0.00006752257,0.00003231249,0.0001215549],"domain_scores_gemma":[0.9995421,0.00008213837,0.00001644891,0.0002880123,0.00003024734,0.0000410649],"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":[0.000007739352,0.000005201633,0.000168981,0.00009577917,0.00001236711,6.821688e-8,0.00009433312,0.9570187,0.0004467825,0.010539,0.002224666,0.02938632],"study_design_scores_gemma":[0.0001761025,0.00001165676,0.00004859609,0.00002559604,0.000004819461,7.023689e-7,0.000002567055,0.9672763,0.0002188001,0.001785524,0.0303578,0.00009154217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001098938,0.0002607745,0.9857707,0.0001825826,0.00007903764,0.001428035,0.000001755939,0.0001470098,0.01103118],"genre_scores_gemma":[0.9350759,0.00006814703,0.06360469,0.0002532959,0.00008067368,0.0006307979,0.000004828722,0.00002790925,0.0002537862],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9339769,"threshold_uncertainty_score":0.2724991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07519798705179835,"score_gpt":0.3259103546780917,"score_spread":0.2507123676262933,"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."}}