{"id":"W2762669156","doi":"10.5539/mas.v11n10p166","title":"Wireless LAN Service Quality Optimization in Academic Environments","year":2017,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mean squared error; Computer science; Adaptive neuro fuzzy inference system; Metric (unit); Terrain; Data mining; Field (mathematics); Test data; Fuzzy logic; Inference; Principal component analysis; Wireless; Artificial intelligence; Statistics; Fuzzy control system; Mathematics; Telecommunications; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001163102,0.000654627,0.0006047687,0.0005252585,0.0003261857,0.001001787,0.0006431328,0.0005042126,0.0005277573],"category_scores_gemma":[0.001957007,0.0002060141,0.0003009559,0.0007489827,0.0004236395,0.0006564835,0.0006800299,0.0004531771,0.0001473123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112189,"about_ca_system_score_gemma":0.0007510862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005907573,"about_ca_topic_score_gemma":0.00419802,"domain_scores_codex":[0.9991608,0.0003156811,0.00003660335,0.000145438,0.0001850474,0.0001564757],"domain_scores_gemma":[0.9993671,0.0002680749,0.0001474289,0.00003307899,0.0001445627,0.00003982067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001026849,0.00008975278,0.002276762,0.00006372387,0.00002794253,0.0000692972,0.00004682251,0.9544528,0.005702181,0.001480399,0.0003247383,0.0353629],"study_design_scores_gemma":[0.00000659691,0.0001059297,0.00116785,0.00000328946,0.000008882347,0.00001502041,0.00005102617,0.9960399,0.001611218,0.0006556085,0.0003297535,0.000005048557],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3823592,0.0009019746,0.608346,0.0004445017,0.00005418176,0.0000854145,0.000117514,0.0006915162,0.006999716],"genre_scores_gemma":[0.9867305,0.0002079296,0.01201513,0.00002336762,0.0000215634,0.00002093398,0.0000504928,0.00001310415,0.0009170795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005907573,"threshold_uncertainty_score":0.01174635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03147347882710709,"score_gpt":0.2807152525500755,"score_spread":0.2492417737229684,"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."}}