{"id":"W2126524517","doi":"10.1109/glocom.2008.ecp.117","title":"Optimal Cell Size in Multi-Hop Cellular Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Hop (telecommunications); Cellular network; Computer network; Context (archaeology); Small cell; Distributed computing","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":[0.0008697149,0.0005266279,0.0006047105,0.0005556306,0.0004174033,0.0007109881,0.0008390992,0.0006138071,0.0007062969],"category_scores_gemma":[0.003956527,0.0003066562,0.0002072915,0.000603209,0.00068786,0.001083901,0.0009947375,0.0003998415,0.0001135163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008830779,"about_ca_system_score_gemma":0.0006734752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001386061,"about_ca_topic_score_gemma":0.001799038,"domain_scores_codex":[0.9993549,0.0002746049,0.00002515543,0.00007995234,0.0001556539,0.0001096759],"domain_scores_gemma":[0.9983585,0.001096288,0.000160545,0.0001306124,0.0001353401,0.0001186652],"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":[0.0001092549,0.00002831699,0.001002677,0.00005366507,0.00001989811,0.00007490269,0.00004969891,0.9373095,0.004658425,0.02476918,0.001001276,0.03092318],"study_design_scores_gemma":[0.00001997038,0.00008257932,0.0005077248,0.000014063,0.00001315058,0.00007267598,0.00004403575,0.9738207,0.002175821,0.02210585,0.00112896,0.00001433572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1923307,0.001852564,0.795357,0.0004319233,0.0001144351,0.00008416119,0.0001685805,0.0002776338,0.009382979],"genre_scores_gemma":[0.942746,0.0005776093,0.0552072,0.00007748303,0.00003807556,0.00009292344,0.00006103379,0.00003566067,0.001163985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001386061,"threshold_uncertainty_score":0.006407142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009735187687416878,"score_gpt":0.1928512593952285,"score_spread":0.1831160717078116,"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."}}