{"id":"W2156681981","doi":"10.1109/tvt.2009.2021180","title":"System Design and Throughput Analysis for Multihop Relaying in Cellular Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Throughput; Computer network; Relay; Computer science; Overhead (engineering); Cellular network; Physical layer; Reuse; Path loss; Spectral efficiency; Wireless; Distributed computing; Engineering; Channel (broadcasting); Telecommunications","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":[0.0009732998,0.0008192811,0.0006249755,0.0008441629,0.0006485008,0.001263123,0.0005158608,0.0006428705,0.005431496],"category_scores_gemma":[0.002821231,0.0003147049,0.0006453463,0.0009033009,0.000501095,0.00100009,0.0004814195,0.0006613542,0.0008137313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00247658,"about_ca_system_score_gemma":0.0008793611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006131992,"about_ca_topic_score_gemma":0.004878898,"domain_scores_codex":[0.998917,0.0004670232,0.00002799479,0.0001186753,0.0003420877,0.0001272596],"domain_scores_gemma":[0.9986776,0.0007735782,0.0001219586,0.00008376066,0.0003194561,0.00002381248],"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":[0.00005001645,0.00002697218,0.0005423032,0.00008538893,0.00003114855,0.0001098734,0.00007421195,0.9563929,0.003733724,0.02593931,0.001197644,0.01181656],"study_design_scores_gemma":[0.00000359966,0.00003070227,0.0002090947,0.000006442559,0.00001134925,0.00003091393,0.00001644724,0.9952483,0.0007263293,0.002899439,0.0008124512,0.000004909183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04099939,0.001271334,0.9413919,0.0003023707,0.00005080753,0.0001459066,0.0002593185,0.0004941113,0.01508476],"genre_scores_gemma":[0.9228952,0.001550707,0.06735054,0.0001184583,0.0001182469,0.0003171918,0.0002727782,0.0001465705,0.007230206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006131992,"threshold_uncertainty_score":0.01817018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234872205798616,"score_gpt":0.2617179702477937,"score_spread":0.2293692481898075,"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."}}