{"id":"W2168745817","doi":"10.5555/1218112.1218516","title":"Wireless network simulation extensions in SIDE/SMURPH","year":2006,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Wireless network; Wireless; Stochastic geometry models of wireless networks; Interference (communication); Wireless ad hoc network; Channel (broadcasting); Computer network; Shadow mapping; Radio resource management; Radio propagation; Network packet; Mobile radio; Telecommunications; Artificial intelligence","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":[0.001769907,0.0008638214,0.0008003379,0.0006331565,0.0004211435,0.001173231,0.002848739,0.001084957,0.02974452],"category_scores_gemma":[0.004721861,0.0007687181,0.001537254,0.0006238353,0.0004440417,0.001791356,0.002620044,0.001960745,0.0107316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004570298,"about_ca_system_score_gemma":0.0009054811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001947545,"about_ca_topic_score_gemma":0.002754337,"domain_scores_codex":[0.999119,0.0003343772,0.00006894724,0.00007316753,0.0003192926,0.00008522817],"domain_scores_gemma":[0.9978706,0.0008954065,0.00008013351,0.0005099883,0.0005381395,0.000105733],"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":[0.0005558095,0.0003488093,0.002052458,0.0009454503,0.0002225659,0.0006849052,0.000633252,0.4719991,0.01083295,0.1800029,0.161045,0.1706768],"study_design_scores_gemma":[0.0001436481,0.00006779387,0.0001934769,0.00009415588,0.00002647885,0.0002678202,0.00002554488,0.7898902,0.004563198,0.03187612,0.172808,0.00004348182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005320022,0.0002643115,0.9150781,0.0005427646,0.0003206198,0.0002477924,0.003033936,0.03136754,0.04382493],"genre_scores_gemma":[0.09596276,0.001158617,0.8337665,0.0009751449,0.0002784211,0.001403007,0.008436195,0.02369968,0.03431969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02974452,"threshold_uncertainty_score":0.09950536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02411231716629415,"score_gpt":0.2696579873759761,"score_spread":0.245545670209682,"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."}}