{"id":"W2022601383","doi":"10.1109/globalsip.2014.7032088","title":"Device-to-device cluster assisted downlink video sharing &amp;#x2014; A base station energy saving approach","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Telecommunications link; Base station; Computer science; Energy consumption; Computer network; Real-time computing; Cellular network; Merge (version control); Cluster (spacecraft); Transmission (telecommunications); Telecommunications; Electrical engineering; Engineering","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":[0.0002514012,0.0007323693,0.0005885897,0.0003891,0.0006138678,0.0006338219,0.001536777,0.0005810731,0.002454294],"category_scores_gemma":[0.0003910228,0.0001495127,0.0004179667,0.0007355259,0.0003257596,0.0006302861,0.0009454952,0.0004309728,0.000425108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005989111,"about_ca_system_score_gemma":0.0006741186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002324113,"about_ca_topic_score_gemma":0.003315743,"domain_scores_codex":[0.9997013,0.00007775737,0.00000779555,0.00007388218,0.00007612719,0.00006308765],"domain_scores_gemma":[0.9997917,0.0000522202,0.00002166858,0.00004715183,0.0000583364,0.00002896],"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":[0.0002856364,0.0002795667,0.001296964,0.0001784632,0.0001445202,0.0003393501,0.0001555278,0.7305228,0.04195687,0.02685207,0.004706368,0.1932819],"study_design_scores_gemma":[0.00001458462,0.0002060284,0.0004896942,0.000006640507,0.00003120559,0.0002092899,0.00009597892,0.9833883,0.008053187,0.004363775,0.003126599,0.0000147118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0679246,0.0004640208,0.9182134,0.0002622482,0.00006116841,0.000101016,0.00007455394,0.0002944675,0.0126045],"genre_scores_gemma":[0.932485,0.0002925156,0.06120088,0.0001281944,0.00004150088,0.00007508205,0.00007766009,0.00002467984,0.005674556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002454294,"threshold_uncertainty_score":0.008210361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087906121965685,"score_gpt":0.2406182142203012,"score_spread":0.2197391530006444,"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."}}