{"id":"W2099177361","doi":"10.1109/vetecf.2009.5379034","title":"Interference Protection on Legacy Devices with Cognitive Radio using Smart Antennas","year":2009,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Prompt (Canada); Université du Québec à Montréal","funders":"","keywords":"Cognitive radio; Interference (communication); Computer science; Mobile ad hoc network; Spectrum management; Computer network; Smart antenna; Radio spectrum; Shadow mapping; Wireless ad hoc network; Antenna (radio); Telecommunications; Directional antenna; Wireless; Channel (broadcasting)","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":[0.0001551237,0.0001879026,0.0001743516,0.0001391325,0.0002019539,0.0003789743,0.0001826773,0.00004258364,0.00000766447],"category_scores_gemma":[0.00002399552,0.00014031,0.00004262914,0.0005003398,0.0000404416,0.001096092,0.00003331783,0.0002075807,0.00001486179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006975163,"about_ca_system_score_gemma":0.00004643451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007256286,"about_ca_topic_score_gemma":0.0000636474,"domain_scores_codex":[0.9988096,0.00007429555,0.0001516545,0.0003973014,0.0002048961,0.0003622374],"domain_scores_gemma":[0.9994383,0.00006803436,0.00008434818,0.0001851612,0.0001279988,0.00009617291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004807692,0.0005157973,0.002256149,0.00001756423,0.0001196745,0.0001911356,0.002021339,0.0003211907,0.005223854,0.03292448,0.00007536198,0.9558527],"study_design_scores_gemma":[0.001655951,0.00383636,0.06130375,0.001626176,0.00004900383,0.0009293148,0.0006570224,0.9057353,0.02146802,0.001375863,0.0002489682,0.001114252],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2732121,0.000043935,0.7189809,0.0003929952,0.0001134135,0.0002332437,2.256079e-7,0.0001528499,0.006870338],"genre_scores_gemma":[0.990234,0.000005452025,0.008604506,0.0009317971,0.0001421186,0.000002292034,7.341546e-7,0.000007417119,0.00007168736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9547384,"threshold_uncertainty_score":0.5721674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0302786291826307,"score_gpt":0.2533380681188706,"score_spread":0.2230594389362399,"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."}}