{"id":"W2079741601","doi":"10.1145/1644893.1644939","title":"Non-intrusive, dynamic interference detection for 802.11 networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Interference (communication); Computer science; Computer network; Wireless network; Wireless; Point (geometry); IEEE 802.11; Distributed computing; Quality (philosophy); Control (management); Telecommunications; Channel (broadcasting); Artificial intelligence","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":[0.001086324,0.0006555798,0.0004779703,0.0007014431,0.0007585739,0.0008829386,0.001063325,0.0006447417,0.001471479],"category_scores_gemma":[0.005604384,0.0004419058,0.000162468,0.0005170164,0.0007857206,0.001888702,0.001108886,0.001107406,0.0007320024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000468776,"about_ca_system_score_gemma":0.0005013926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000656132,"about_ca_topic_score_gemma":0.001213126,"domain_scores_codex":[0.9984181,0.0003491687,0.00006389386,0.0002096348,0.0008420035,0.0001172222],"domain_scores_gemma":[0.9978154,0.0009683666,0.0003020906,0.0004420818,0.0003992681,0.0000727185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008982747,0.0003104748,0.008593247,0.0003780058,0.00007662149,0.0005057308,0.0004806074,0.04980029,0.1560546,0.03984516,0.008223263,0.7348337],"study_design_scores_gemma":[0.00006086694,0.0008179891,0.006727905,0.000130904,0.00007934224,0.002632709,0.0002695642,0.7983036,0.1208109,0.03671419,0.03329805,0.0001540457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04240908,0.002270845,0.9453244,0.0003952793,0.0001901332,0.00008616325,0.00007711186,0.00173086,0.007516114],"genre_scores_gemma":[0.8248813,0.001186353,0.1675917,0.0002056867,0.0001502619,0.00009968734,0.0001602153,0.00008445981,0.005640444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001471479,"threshold_uncertainty_score":0.005745113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008898956894515211,"score_gpt":0.2578967457718702,"score_spread":0.248997788877355,"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."}}