{"id":"W2441111165","doi":"10.1109/mownet.2016.7496622","title":"Performance evaluation of IoT protocols under a constrained wireless access network","year":2016,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Queen's University","funders":"","keywords":"MQTT; Computer science; Computer network; Message queue; Network packet; Wireless; Wireless network; Latency (audio); Reliability (semiconductor); Bandwidth (computing); Default gateway; Packet loss; Communications protocol; Wireless sensor network; Distributed computing; Internet of Things; Embedded system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001263539,0.00009621397,0.0001361769,0.00004656994,0.00006932947,0.00007408028,0.0007344457,0.00004458725,0.0000181315],"category_scores_gemma":[0.00002055421,0.00006081398,0.00003591421,0.0003140386,0.00005994086,0.000385837,0.0002666539,0.00004168023,0.00001906243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004496951,"about_ca_system_score_gemma":0.0002323719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003545614,"about_ca_topic_score_gemma":0.000001176853,"domain_scores_codex":[0.9987103,0.00009465863,0.0002521933,0.0002355485,0.000439979,0.0002673017],"domain_scores_gemma":[0.999086,0.0001113196,0.0001338385,0.000356663,0.0002658183,0.00004634776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001267266,0.00004944478,0.01041635,0.00002907432,0.00002193871,4.282067e-7,0.0001107044,0.001428639,0.001246967,0.00784341,0.007863996,0.9709764],"study_design_scores_gemma":[0.001777457,0.000150081,0.03078913,0.0004478384,0.00001236738,0.000008697424,0.000005133978,0.9489391,0.01106577,0.004371075,0.002126163,0.0003071492],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4108932,0.00000742201,0.5439807,0.0008234354,0.001980476,0.006745556,9.712991e-8,0.0001928771,0.03537625],"genre_scores_gemma":[0.9938696,5.226096e-7,0.004295344,0.0001361799,0.0008136364,0.0006675589,2.957857e-7,0.000005738033,0.0002111486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9706692,"threshold_uncertainty_score":0.2479922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09536353673627278,"score_gpt":0.3541576420735985,"score_spread":0.2587941053373257,"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."}}