{"id":"W2045053428","doi":"10.1109/netwks.2008.4763669","title":"Impact of Bandwidth Demand Growth on HFC Network","year":2008,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Bandwidth (computing); Dynamic bandwidth allocation; Computer science; Computer network; On demand; Telecommunications; Multimedia","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":[0.0009810171,0.0004553771,0.0003101057,0.0008461666,0.0008632129,0.001734235,0.0006950861,0.001734415,0.007677542],"category_scores_gemma":[0.006531965,0.0001776846,0.0002625671,0.00158266,0.00073189,0.002429473,0.001029303,0.001379552,0.001208386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003096618,"about_ca_system_score_gemma":0.0009627257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02504028,"about_ca_topic_score_gemma":0.01830973,"domain_scores_codex":[0.9984654,0.0003065258,0.00002931065,0.0001181689,0.0005616343,0.0005189471],"domain_scores_gemma":[0.990356,0.005707311,0.0005949977,0.0002378324,0.002547904,0.0005559477],"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":[0.002598284,0.0006017963,0.1333957,0.0004721729,0.0001043863,0.008905103,0.0007715155,0.488803,0.0361709,0.08980231,0.1074597,0.1309152],"study_design_scores_gemma":[0.0001145428,0.0007714321,0.1618695,0.0002882906,0.000151064,0.004742685,0.008281284,0.6404244,0.04179595,0.03930068,0.1019909,0.0002693326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8562512,0.001726941,0.004446478,0.01436384,0.0006860524,0.00003405321,0.003233822,0.0003404412,0.1189172],"genre_scores_gemma":[0.9947188,0.0005848957,0.0002787404,0.0004719473,0.0001061841,0.000007894921,0.0006330288,0.00005075649,0.003147867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02504028,"threshold_uncertainty_score":0.04978901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547799234721585,"score_gpt":0.238116099744562,"score_spread":0.2226381073973462,"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."}}