{"id":"W2100937320","doi":"10.5555/1995456.1995889","title":"Simulation of large wireless sensor networks using Cell-DEVS","year":2009,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Wireless sensor network; DEVS; Computer science; Key distribution in wireless sensor networks; Mobile wireless sensor network; Wireless; Wireless ad hoc network; Formalism (music); Computer network; Topology control; Distributed computing; Wireless network; Real-time computing; Embedded system; Modeling and simulation; Simulation; 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":[0.0008340655,0.0004969896,0.0008692979,0.0005764491,0.000634344,0.0008359792,0.001393124,0.001002721,0.002413402],"category_scores_gemma":[0.002989942,0.0003378456,0.0007380293,0.0009370088,0.0006797066,0.0006219352,0.0007538807,0.0008543053,0.0002040085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009874296,"about_ca_system_score_gemma":0.000819904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01581637,"about_ca_topic_score_gemma":0.008223554,"domain_scores_codex":[0.9996649,0.0001221041,0.00002206603,0.00003903038,0.00008458749,0.00006726226],"domain_scores_gemma":[0.9973136,0.001952417,0.0001605735,0.0001475057,0.0002854446,0.0001404482],"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":[0.00001630061,0.00001660961,0.0005415198,0.0000133393,0.000009297104,0.00002334841,0.0000212852,0.9949433,0.0002311513,0.003295556,0.000113828,0.0007743255],"study_design_scores_gemma":[0.00000440083,0.000004968901,0.00005308882,0.000001427058,0.000001679814,0.000003368449,0.000006198984,0.9991487,0.0001490931,0.0004807615,0.0001443518,0.000001909506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6544303,0.0006966243,0.3200517,0.0008945593,0.0002175351,0.0002002686,0.002352132,0.001172811,0.01998422],"genre_scores_gemma":[0.938179,0.0004081034,0.05708016,0.0001194669,0.00002155475,0.0003701256,0.001119598,0.00008510648,0.002616792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01581637,"threshold_uncertainty_score":0.0314486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1398553753932603,"score_gpt":0.431091446718514,"score_spread":0.2912360713252538,"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."}}