{"id":"W2168241011","doi":"10.1109/iscc.2006.46","title":"Capacity Enhancement in CDMA Cellular Networks using Multi-hop Communication","year":2006,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Cellular network; Telecommunications link; Computer science; Interference (communication); Base station; Computer network; Code division multiple access; Near-far problem; Hop (telecommunications); Spread spectrum; Electronic engineering; Engineering; Channel (broadcasting)","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":[0.0007934213,0.0004544547,0.0003366174,0.0006504668,0.0003037644,0.0008756517,0.0005570989,0.0005451955,0.0007808194],"category_scores_gemma":[0.00407457,0.0002001443,0.0002238917,0.0006850887,0.001213611,0.001113469,0.0007438148,0.0005264457,0.0001469261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001007161,"about_ca_system_score_gemma":0.0005555824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001122442,"about_ca_topic_score_gemma":0.0009977578,"domain_scores_codex":[0.9989024,0.0003806478,0.00002167509,0.00007485243,0.0004583601,0.0001620986],"domain_scores_gemma":[0.997261,0.001935175,0.0001994462,0.0002111237,0.0003357664,0.00005742702],"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":[0.0001247163,0.00006146259,0.001213185,0.0002401885,0.00004270813,0.0004149158,0.0002370221,0.7762136,0.0501909,0.1205539,0.0008784321,0.04982889],"study_design_scores_gemma":[0.000008278143,0.0001067413,0.0006176805,0.0000276021,0.00002248971,0.0002005461,0.00004930471,0.9502882,0.01404281,0.03226133,0.002352556,0.00002259303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2621626,0.007090624,0.6973656,0.0005958547,0.00009460501,0.00004474215,0.00007484564,0.0005998709,0.03197122],"genre_scores_gemma":[0.9807476,0.0009500668,0.01721234,0.00004883583,0.00003529778,0.00002031393,0.00001437626,0.00002034503,0.0009507022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001122442,"threshold_uncertainty_score":0.00730747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06948685118996231,"score_gpt":0.2816990549275925,"score_spread":0.2122122037376301,"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."}}