{"id":"W3011857286","doi":"10.1109/gcwkshps45667.2019.9024527","title":"Multi Objective Resource Allocation for Joint eMBB and URLLC Traffic with Different QoS Requirements","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Quality of service; Computer network; Telecommunications link; Cellular network; Mobile broadband; Latency (audio); Reliability (semiconductor); Resource allocation; Distributed computing; Wireless; 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":[0.00004936075,0.0001307701,0.0001465286,0.00005529595,0.0000308422,0.00001898444,0.00003547552,0.00004551619,0.00001013885],"category_scores_gemma":[0.00000942187,0.0001040431,0.00001700882,0.00005501787,0.000009681768,0.0001444058,0.00001012573,0.00004375826,0.000006182799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009876819,"about_ca_system_score_gemma":0.000004350694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002976789,"about_ca_topic_score_gemma":0.00003527567,"domain_scores_codex":[0.9994245,0.000009974407,0.0001561641,0.0001863035,0.00007324503,0.0001497866],"domain_scores_gemma":[0.9997045,0.00002475,0.00003551347,0.0001497702,0.00004431182,0.00004111976],"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":[0.00003961379,0.00003141517,0.0004507295,0.0001983702,0.00005951176,2.439126e-7,0.0009106662,0.9784063,0.01682987,0.0001036907,0.0001563659,0.002813284],"study_design_scores_gemma":[0.001835881,0.0001616834,0.001882696,0.00009810619,0.00001918274,0.000003611219,0.0007906199,0.9856648,0.008962127,0.000005813584,0.0003404355,0.0002350779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3407719,0.00005636878,0.6571055,0.00001604856,0.0001055537,0.001079386,0.000003414852,0.00021673,0.0006451326],"genre_scores_gemma":[0.9771025,0.000007139817,0.02156635,0.0000144214,0.00003372322,0.0001075727,0.0000259067,0.00004176776,0.001100617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6363306,"threshold_uncertainty_score":0.4242755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0157376100380902,"score_gpt":0.2239883575392131,"score_spread":0.2082507475011229,"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."}}