{"id":"W1527824420","doi":"","title":"A performance analysis of multi-hop ad hoc networks with adaptive antenna array systems","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Polytechnique Montréal","funders":"","keywords":"Aloha; Stochastic geometry; Computer science; Wireless ad hoc network; Network packet; Hop (telecommunications); Relay; Computer network; Upper and lower bounds; Node (physics); Wireless; Throughput; Topology (electrical circuits); Telecommunications; Mathematics; Statistics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003524494,0.0004461226,0.0009186495,0.0004843911,0.0001613704,0.0001315543,0.001964733,0.0005140491,0.00001104783],"category_scores_gemma":[0.000006592199,0.0004193167,0.000350582,0.002521268,0.00019584,0.000369578,0.0009126455,0.001116147,0.000008638603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009986588,"about_ca_system_score_gemma":0.0002657986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009596346,"about_ca_topic_score_gemma":0.0003771647,"domain_scores_codex":[0.99752,0.0001997599,0.0003457075,0.001276376,0.0001686245,0.00048954],"domain_scores_gemma":[0.9964248,0.0001297229,0.0007598012,0.001895422,0.0005821744,0.0002080564],"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":[0.0001381571,0.0001098974,0.008239197,0.00008893869,0.00117451,0.0001253461,0.0001955239,0.9860587,0.00003123917,0.002947037,0.00001709503,0.0008744336],"study_design_scores_gemma":[0.0005549931,0.0001592277,0.005750142,0.0003275675,0.0006256754,0.000004395944,0.00005607746,0.9917108,0.00002932593,0.00004985358,0.0002281298,0.0005037739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1132977,0.0002952893,0.8836288,0.00001072037,0.0003502969,0.001910618,0.00002301053,0.0001343483,0.0003491702],"genre_scores_gemma":[0.9930502,0.0005626135,0.005526247,0.00002135052,0.00006656396,0.00004502959,0.00001964652,0.0000235035,0.0006848891],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8797525,"threshold_uncertainty_score":0.9998259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05425823955820821,"score_gpt":0.1900705502256718,"score_spread":0.1358123106674636,"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."}}