{"id":"W7017314501","doi":"","title":"Adaptive Sensing Strategies for Opportunistic Spectrum Access","year":2013,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cognitive radio; Channel (broadcasting); Key (lock); Detector; Idle; State (computer science)","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":[0.001019237,0.0007490637,0.0005711776,0.0005145761,0.0005135525,0.0008650973,0.001371764,0.0008058785,0.002407442],"category_scores_gemma":[0.003438565,0.0003499794,0.0003386392,0.0004272366,0.001005575,0.001035626,0.001235189,0.0008029501,0.0003751549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007003506,"about_ca_system_score_gemma":0.0007596054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00177486,"about_ca_topic_score_gemma":0.001765639,"domain_scores_codex":[0.9992403,0.0002396376,0.00003799559,0.0001340348,0.0002292656,0.0001187344],"domain_scores_gemma":[0.9985689,0.0008802817,0.0001492755,0.0001175525,0.0002043162,0.00007969518],"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":[0.0001768762,0.0001123648,0.0006455044,0.0001842626,0.00007231402,0.0005200229,0.0003142543,0.5848278,0.01246177,0.310898,0.004299562,0.08548731],"study_design_scores_gemma":[0.00001832346,0.00004294978,0.00009439114,0.00001344236,0.000007798476,0.00007935208,0.00002949014,0.9556212,0.0004718445,0.0411652,0.002442957,0.00001312747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0135224,0.0008969199,0.9693871,0.0003489981,0.0001179741,0.0001357055,0.00004777857,0.0002262204,0.01531682],"genre_scores_gemma":[0.9027554,0.0008183399,0.08835236,0.0002364505,0.000112426,0.0003354226,0.00005876778,0.000039803,0.00729101],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002407442,"threshold_uncertainty_score":0.00805366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011314216066645,"score_gpt":0.1862902527267215,"score_spread":0.1761771105660551,"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."}}