{"id":"W1590520640","doi":"10.1023/a:1008918530685","title":"An Efficient ARQ Protocol for Adaptive Error Control over Time-Varying Channels","year":2001,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science","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":[0.002008059,0.0007339449,0.0008314771,0.0006062863,0.0006460589,0.001053352,0.00143923,0.0009551335,0.002365696],"category_scores_gemma":[0.003484598,0.0003580318,0.0003666308,0.0005560478,0.0007491733,0.001193325,0.001242548,0.00134809,0.0009401029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004628843,"about_ca_system_score_gemma":0.000850744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008702908,"about_ca_topic_score_gemma":0.001745331,"domain_scores_codex":[0.9985452,0.0004066533,0.00008988263,0.0001541153,0.0006683266,0.0001359274],"domain_scores_gemma":[0.9981453,0.0008531439,0.0001077717,0.0003829156,0.0004694138,0.00004142682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000982188,0.000299332,0.0004451987,0.0002963634,0.0001632095,0.0004302553,0.0003628479,0.1309903,0.1343178,0.1886924,0.008237653,0.5347824],"study_design_scores_gemma":[0.000180599,0.0003183792,0.0002352274,0.00002298015,0.00007914987,0.0002983887,0.00002546826,0.9442218,0.02313192,0.02295202,0.00847716,0.00005680421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004041935,0.0002136452,0.9942335,0.00008813427,0.00009825949,0.00005647779,0.00002101157,0.0004462449,0.0008007223],"genre_scores_gemma":[0.3175666,0.0005817437,0.6727665,0.0003653888,0.000278067,0.0003429445,0.0001646835,0.0001223252,0.007811751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002365696,"threshold_uncertainty_score":0.01061982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0939484817847611,"score_gpt":0.3679023312612069,"score_spread":0.2739538494764457,"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."}}