{"id":"W1972456124","doi":"10.1007/s11276-007-0077-y","title":"An efficient delay constrained scheduling scheme for IEEE 802.16 networks","year":2007,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scheduling (production processes); Adaptability; Queue; Scheme (mathematics); Simple (philosophy); Distributed computing; Real-time computing; Computer network; Mathematical optimization; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007987336,0.0005707349,0.0005505184,0.000176645,0.0003329742,0.0001109966,0.0004229948,0.0005744465,0.00002859929],"category_scores_gemma":[0.00001908632,0.0006430483,0.0001775382,0.0007261652,0.0001586734,0.0002594968,0.00003379242,0.0006386113,0.000007132446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003105248,"about_ca_system_score_gemma":0.00003185346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004087919,"about_ca_topic_score_gemma":0.00005285909,"domain_scores_codex":[0.9967488,0.00004224619,0.0008173331,0.0006272223,0.0002845252,0.001479867],"domain_scores_gemma":[0.9981784,0.0003954391,0.0001722776,0.0006210607,0.0002099444,0.0004229111],"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":[0.00010924,0.00006317772,0.000192006,0.00003695602,0.00007037453,0.00001295185,0.00005904181,0.9603119,0.000431772,0.001344843,0.0003056827,0.03706202],"study_design_scores_gemma":[0.001260149,0.00007738115,0.00005818106,0.0001396036,0.00003870709,0.00001909559,0.00009555892,0.996542,0.0004914346,0.00004184463,0.0004959463,0.0007401388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1231425,0.001052045,0.8712265,0.00001203559,0.002021604,0.0008030739,0.000009024064,0.001265478,0.0004676672],"genre_scores_gemma":[0.9254649,0.0002105769,0.07137024,0.0001282166,0.002216225,0.0001031808,0.0002314603,0.000247904,0.00002728116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8023224,"threshold_uncertainty_score":0.9996021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00811876012927952,"score_gpt":0.2395873011992318,"score_spread":0.2314685410699523,"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."}}