{"id":"W2782419828","doi":"10.48550/arxiv.1801.00394","title":"Generalized Compression Strategy for the Downlink Cloud Radio Access Network","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Telecommunications link; Computer network; Radio access network; Relay; Broadcasting (networking); Transmission (telecommunications); Base station; Telecommunications; Power (physics); Mobile station","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006658061,0.001002899,0.0006455086,0.0004855919,0.0003999424,0.001006226,0.0007118899,0.0006950698,0.001585364],"category_scores_gemma":[0.00226179,0.000175821,0.0003519083,0.0005634932,0.001014029,0.001254612,0.0008878312,0.0007940964,0.000192526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338054,"about_ca_system_score_gemma":0.0008741324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002782889,"about_ca_topic_score_gemma":0.001698656,"domain_scores_codex":[0.9994445,0.0001445216,0.00002038033,0.00009931193,0.0001855611,0.0001057851],"domain_scores_gemma":[0.9990269,0.0005947985,0.0001101834,0.00007767631,0.0001497399,0.00004074202],"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":[0.000164252,0.00006979871,0.0004413121,0.0001565853,0.00004514128,0.0004604783,0.0002128456,0.7153578,0.01581279,0.2036635,0.001636601,0.06197881],"study_design_scores_gemma":[0.00001727919,0.00009785939,0.0001537562,0.00001435998,0.00001551637,0.000174034,0.00004467801,0.9729928,0.002712237,0.02252261,0.001238981,0.0000157998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06579737,0.001234153,0.917012,0.0004447046,0.00004675105,0.0001196457,0.0000947188,0.0001552002,0.01509548],"genre_scores_gemma":[0.9407616,0.0009932639,0.05401975,0.0001882495,0.00008765332,0.0001214884,0.00008199936,0.00002721507,0.003718767],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002782889,"threshold_uncertainty_score":0.009708285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2226090628470401,"score_gpt":0.2727051682131573,"score_spread":0.05009610536611714,"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."}}