{"id":"W3215165863","doi":"","title":"Selective Active Scanning for Fast Handoff in WLAN using Sensor Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Handover; Computer science; Latency (audio); Quality of service; Wireless sensor network; Process (computing); Real-time computing; 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":[0.0002431851,0.0001454723,0.0002004465,0.00009172411,0.000146857,0.0001485862,0.0002915525,0.00009065141,0.000008593782],"category_scores_gemma":[0.00001209057,0.0001305795,0.00006024694,0.0004409794,0.00002071283,0.0004918845,0.0001038095,0.0001716688,0.000003318966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001267873,"about_ca_system_score_gemma":0.0000644845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007568489,"about_ca_topic_score_gemma":0.0001940641,"domain_scores_codex":[0.9987997,0.00005782273,0.0002050015,0.000366764,0.0001112282,0.0004594262],"domain_scores_gemma":[0.9993847,0.0001703305,0.00008118695,0.000208717,0.00008116752,0.0000738737],"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":[0.0001404245,0.0000950216,0.002262453,0.00001428295,0.00003570577,0.00000603114,0.001589344,0.7401655,0.0008851678,0.006632624,0.001000399,0.247173],"study_design_scores_gemma":[0.0007514633,0.00006302633,0.001354841,0.00005728893,0.000002106153,0.000006285207,0.00004225932,0.994291,0.001732552,0.0002317019,0.001279554,0.0001879195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008825517,0.00002612367,0.9856789,0.0002743528,0.00009050711,0.003402672,0.000001087308,0.00009195309,0.001608948],"genre_scores_gemma":[0.8262016,0.000001928506,0.1714869,0.0004318183,0.0005364786,0.001033596,0.000001499376,0.00001578037,0.0002903993],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8173761,"threshold_uncertainty_score":0.5324876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02566466729957771,"score_gpt":0.2932826840364073,"score_spread":0.2676180167368296,"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."}}