{"id":"W2337942997","doi":"10.1109/access.2016.2553150","title":"On Enhancing Technology Coexistence in the IoT Era: ZigBee and 802.11 Case","year":2016,"lang":"en","type":"article","venue":"IEEE Access","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"NeuRFon; Computer science; Computer network; Interoperability; Internet of Things; Prioritization; Wireless; Wireless network; Embedded system; Telecommunications; Key distribution in wireless sensor networks; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001711188,0.0006526709,0.0004012534,0.0009882692,0.001274732,0.002911029,0.000781315,0.00249191,0.00238632],"category_scores_gemma":[0.006017561,0.000481624,0.0005687629,0.001048521,0.002999318,0.007312308,0.002127361,0.00148378,0.0003980077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151046,"about_ca_system_score_gemma":0.0008848883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002326675,"about_ca_topic_score_gemma":0.001977617,"domain_scores_codex":[0.9984977,0.0006312679,0.000040859,0.0001308911,0.0004224541,0.0002769058],"domain_scores_gemma":[0.9969918,0.002061971,0.0002781761,0.0002344699,0.000270045,0.0001635795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005398691,0.00007913789,0.001827358,0.00008617983,0.00002095902,0.0007107239,0.0004066365,0.0393481,0.001729325,0.9239612,0.001551452,0.0302249],"study_design_scores_gemma":[0.0000348579,0.0002150264,0.001300585,0.0001548148,0.0000491398,0.001420968,0.0007374686,0.4188159,0.002215438,0.552105,0.02287959,0.00007133753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1364662,0.01573051,0.636319,0.01145985,0.0007155659,0.000120489,0.00005505426,0.0001842802,0.198949],"genre_scores_gemma":[0.9514221,0.00625527,0.03418424,0.0004823128,0.0005063443,0.00007063156,0.00001506164,0.00003809836,0.007026095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002911029,"threshold_uncertainty_score":0.009049773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02885663479460117,"score_gpt":0.3132325811120683,"score_spread":0.2843759463174671,"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."}}