{"id":"W2163193980","doi":"10.1109/tns.2009.2037622","title":"Receiver-Assisted Congestion Control to Achieve High Throughput in Lossy Wireless Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Network congestion; Computer science; Computer network; Lossy compression; Packet loss; Wireless network; Timeout; Throughput; Bandwidth (computing); Real-time computing; Wireless; Network packet; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002663242,0.0008135817,0.0006909941,0.0009892026,0.0007585832,0.0009212655,0.001745144,0.0005284262,0.0008751479],"category_scores_gemma":[0.006303534,0.000357571,0.0002596554,0.0006298666,0.0008730757,0.001860586,0.0009382488,0.00112446,0.0002010659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006114802,"about_ca_system_score_gemma":0.0007284071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112541,"about_ca_topic_score_gemma":0.00108424,"domain_scores_codex":[0.9990845,0.0002630036,0.00006503348,0.0001379032,0.0003268158,0.000122829],"domain_scores_gemma":[0.9972228,0.001402408,0.0004392762,0.0003243613,0.0005164992,0.00009473785],"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":[0.000532323,0.0005306281,0.003076894,0.0005286032,0.0002107651,0.0004642428,0.0005851501,0.5646362,0.1358302,0.06998887,0.005164289,0.218452],"study_design_scores_gemma":[0.00007370568,0.0002911421,0.0004109915,0.0000196783,0.0000621501,0.0001596651,0.00001904237,0.963805,0.02099956,0.01062914,0.00349494,0.00003490709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04788396,0.001230364,0.9471076,0.0002133908,0.0001436535,0.0001139144,0.00001854908,0.001516626,0.001772023],"genre_scores_gemma":[0.8848102,0.0006831322,0.1123748,0.0001566197,0.0001977222,0.0001505905,0.00003781578,0.0001108286,0.001478246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002663242,"threshold_uncertainty_score":0.01408476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006130692222795203,"score_gpt":0.2168857200105535,"score_spread":0.2107550277877583,"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."}}