{"id":"W2104354412","doi":"10.1109/tnet.2008.2005219","title":"Delay Aware Link Scheduling for Multi-Hop TDMA Wireless Networks","year":2008,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":161,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Time division multiple access; Computer network; Scheduling (production processes); Router; Transmission delay; Wireless network; Distributed computing; Wireless; Mathematical optimization; Network packet; 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","sts"],"consensus_categories":[],"category_scores_codex":[0.000536221,0.0005815789,0.0005788429,0.0002360136,0.001702481,0.0002304551,0.002006205,0.0004732539,0.00001670786],"category_scores_gemma":[0.0000123185,0.0006263771,0.000471279,0.001215567,0.0001430773,0.0006351276,0.00004063512,0.001099102,0.00003369396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002083737,"about_ca_system_score_gemma":0.0001551488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002639136,"about_ca_topic_score_gemma":0.0001024793,"domain_scores_codex":[0.9960136,0.0001677544,0.0007802419,0.001226293,0.0004803575,0.001331743],"domain_scores_gemma":[0.9964725,0.0008396753,0.000278509,0.001805575,0.0002448225,0.0003588786],"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":[0.00003837807,0.0001286705,0.00009992158,0.0000154169,0.00008436234,0.00004933589,0.0002696796,0.7576395,0.00003408938,0.0002225886,0.0002176457,0.2412004],"study_design_scores_gemma":[0.001304812,0.0001967638,0.00008066962,0.0002430325,0.00004384622,0.0001456129,0.00001985852,0.9904557,0.0003008616,0.0001802756,0.006347666,0.0006808595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004332479,0.0006325388,0.9862902,0.0004343365,0.006331661,0.0009761995,0.000005847435,0.0009220662,0.00007463873],"genre_scores_gemma":[0.8081184,0.0006619347,0.1874116,0.0006410347,0.002289378,0.000427306,0.00001036415,0.0001088565,0.0003310937],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8037859,"threshold_uncertainty_score":0.9996188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05488659881913505,"score_gpt":0.2781040589740816,"score_spread":0.2232174601549466,"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."}}