{"id":"W2034974601","doi":"10.1109/iscc.2008.4625659","title":"An efficient rate adaptation scheme for multihop wireless networks using Kalman Filter","year":2008,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Concordia University","funders":"","keywords":"Computer science; Kalman filter; Transmission (telecommunications); Computer network; Channel (broadcasting); Wireless ad hoc network; Network packet; Throughput; Transmitter; Extended Kalman filter; Real-time computing; Data transmission; Interference (communication); Wireless; Telecommunications; Artificial intelligence","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":[0.0003676674,0.000176886,0.0001853641,0.00006171294,0.0003970259,0.0001361657,0.0005366997,0.0001001691,0.00001443236],"category_scores_gemma":[0.00000649481,0.0001538266,0.00008097815,0.0002869467,0.0000436095,0.0003964986,0.00008589937,0.0001074286,0.000006487715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003656489,"about_ca_system_score_gemma":0.00006390437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005310266,"about_ca_topic_score_gemma":0.00001593062,"domain_scores_codex":[0.9985844,0.00009098581,0.0002743759,0.0004585796,0.0001667232,0.0004249189],"domain_scores_gemma":[0.9990664,0.0001161468,0.000111887,0.0004203669,0.0001474329,0.0001377951],"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":[0.00003121726,0.0001021672,0.0001916175,0.00001012089,0.000009623783,0.000007584523,0.0004332517,0.9751987,0.00109429,0.006933341,0.0004972558,0.01549082],"study_design_scores_gemma":[0.000621189,0.0001113291,0.0006344811,0.00002630508,0.000002556275,0.00001101799,0.0000162724,0.9966094,0.0008407358,0.00007073951,0.0008189417,0.0002369598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1138192,0.00002166869,0.8826596,0.00006405709,0.0001900432,0.002969622,0.000001109618,0.0001746662,0.0001000465],"genre_scores_gemma":[0.7636532,0.000003563473,0.234809,0.000349174,0.0002704525,0.0007785736,0.000006596053,0.00001752078,0.0001118908],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.649834,"threshold_uncertainty_score":0.6272866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06258685120567083,"score_gpt":0.2945059056725254,"score_spread":0.2319190544668546,"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."}}