{"id":"W2073860680","doi":"10.1109/aina.2014.36","title":"A Wi-Fi Simulation Model Which Supports Channel Scanning across Multiple Non-overlapping Channels in NS3","year":2014,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Channel (broadcasting); Wireless; Selection (genetic algorithm); Computer network; Wireless network; Telecommunications; Machine learning","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":[0.0007711634,0.0006526759,0.000476378,0.0003964214,0.0006962263,0.0006131139,0.001620432,0.0007195837,0.005254029],"category_scores_gemma":[0.001590669,0.0003705033,0.0005120541,0.0005619156,0.0003885449,0.0008547759,0.0005044026,0.00116503,0.001238111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006251461,"about_ca_system_score_gemma":0.001412523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01409664,"about_ca_topic_score_gemma":0.0116013,"domain_scores_codex":[0.9997087,0.0000888437,0.0000295573,0.00002752711,0.00009822076,0.00004716883],"domain_scores_gemma":[0.9992269,0.000285253,0.0000480476,0.0001728717,0.0002094203,0.00005756723],"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":[0.0002978283,0.0002481891,0.002511969,0.0001638439,0.00006832963,0.0001407644,0.0002300746,0.9407153,0.01086299,0.01464805,0.01074118,0.01937151],"study_design_scores_gemma":[0.00004208361,0.00004121348,0.0002800249,0.00001220565,0.00001679007,0.00003328951,0.00001898891,0.982204,0.004383274,0.001389132,0.01155996,0.00001920286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1209684,0.0001942631,0.8086163,0.0007278656,0.0003395608,0.001089282,0.008482707,0.02137229,0.03820923],"genre_scores_gemma":[0.5814437,0.0006185346,0.3885674,0.0003669062,0.00005252414,0.002067201,0.01005121,0.001753929,0.01507845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01409664,"threshold_uncertainty_score":0.0280292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481939820534318,"score_gpt":0.2946160902172113,"score_spread":0.2697966920118681,"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."}}