{"id":"W3036521752","doi":"10.1109/ants47819.2019.9118081","title":"An Evaluation of the Proportional Fair Scheduler in a Physically Deployed LTE-A Network","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Computer network; Network scheduler; Proportionally fair; Quality of service; Dynamic priority scheduling; Round-robin scheduling","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":[0.0002500702,0.00007636222,0.00009700959,0.00002303225,0.00001371535,0.000005971527,0.0001022537,0.00004357965,0.0001173872],"category_scores_gemma":[0.00001172785,0.0000580037,0.00002658228,0.0003225194,0.00001462005,0.0002050079,0.0000111832,0.00008908763,0.00001020572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006514444,"about_ca_system_score_gemma":0.00003429379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002736394,"about_ca_topic_score_gemma":0.00004517889,"domain_scores_codex":[0.9992039,0.00005115405,0.0001867027,0.0001104936,0.0003158236,0.0001319305],"domain_scores_gemma":[0.9995968,0.00001861793,0.00004118175,0.0002211418,0.0001042146,0.00001804685],"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":[0.000005128985,0.0000241618,0.01579995,0.000008198152,0.000006678771,2.894879e-8,0.00002884472,0.9774019,0.002032396,0.001837339,0.00006701521,0.002788344],"study_design_scores_gemma":[0.0003163958,0.00001214731,0.06068871,0.00002716062,0.000007366963,2.194593e-7,0.000012558,0.9363187,0.001153657,0.001376901,0.00001530037,0.00007090392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9431805,0.00003435618,0.05375145,0.00002325398,0.0001900742,0.0005297634,6.369222e-7,0.0001007681,0.00218919],"genre_scores_gemma":[0.9927205,0.00000391168,0.007090311,0.00001850634,0.00007632148,0.00003257626,0.00001160039,0.00002186849,0.00002443449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04953996,"threshold_uncertainty_score":0.2365322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007608259629789648,"score_gpt":0.2303468917854315,"score_spread":0.2227386321556418,"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."}}