{"id":"W2164602038","doi":"10.1109/iscit.2009.5341290","title":"On the throughput gain for rapid dynamic symbol duration adaptation within discrete duration sets","year":2009,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Symbol (formal); Adaptation (eye); Duration (music); Throughput; Computer science; Set (abstract data type); Focus (optics); Algorithm; Telecommunications; Wireless","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":[0.001102392,0.0001474857,0.0001189224,0.00009215763,0.0004842903,0.0003903187,0.001096736,0.00007510331,0.00001968497],"category_scores_gemma":[0.0002552443,0.00009948673,0.00006591067,0.0004467733,0.00004351238,0.0008445235,0.00008765628,0.0002078159,0.00004325624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139357,"about_ca_system_score_gemma":0.00008859918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001021294,"about_ca_topic_score_gemma":0.00008256731,"domain_scores_codex":[0.9981815,0.000343844,0.0004064865,0.0003435389,0.000462988,0.0002616367],"domain_scores_gemma":[0.9976709,0.0007678483,0.0001911892,0.001106224,0.0002095976,0.00005423707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000556607,0.00007910673,0.000003569471,0.000006688412,0.00001455881,7.05174e-7,0.002607719,0.04865175,0.002118149,0.8573957,0.003522364,0.08554405],"study_design_scores_gemma":[0.0002579498,0.0002284524,0.0005645793,0.00002235,0.000002516722,0.000002388829,0.0001789742,0.960634,0.001303518,0.03655939,0.0001169128,0.0001289785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01076888,0.00004282151,0.9469047,0.03928079,0.0001163033,0.0009976956,0.000002219138,0.0001906408,0.001695941],"genre_scores_gemma":[0.9620578,0.00004816963,0.03606492,0.001191311,0.00003104092,0.0001360648,0.00005417221,0.000009817843,0.0004067421],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9512889,"threshold_uncertainty_score":0.4056951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03942417142665731,"score_gpt":0.3151542908873872,"score_spread":0.2757301194607298,"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."}}