{"id":"W2042601059","doi":"10.1109/iwcmc.2011.5982582","title":"Performance of simple cognitive personal area networks with finite buffers","year":2011,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Piconet; Network packet; Computer science; Computer network; Scheduling (production processes); Transmission (telecommunications); Node (physics); Simple (philosophy); Real-time computing; Bluetooth; Wireless; Telecommunications; Mathematical optimization; Engineering; Mathematics","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":[0.0001298935,0.0001545871,0.0001942025,0.00007157778,0.0001035992,0.00003070822,0.0002200325,0.00004467395,0.0001217733],"category_scores_gemma":[0.0000104545,0.0001169768,0.00005487445,0.000377177,0.0001240315,0.0003157307,0.00008510578,0.0001422847,0.000006530875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001481548,"about_ca_system_score_gemma":0.00004337566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005670173,"about_ca_topic_score_gemma":0.0000525936,"domain_scores_codex":[0.9989763,0.00003208869,0.0001628415,0.0003017672,0.0001942474,0.0003327907],"domain_scores_gemma":[0.9992775,0.0002205998,0.00009167256,0.0001630855,0.0001561359,0.00009095399],"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":[0.001092187,0.0005423551,0.2069294,0.00006628694,0.0005178733,0.000244652,0.01277646,0.004054051,0.0001128305,0.007707446,0.0006620545,0.7652944],"study_design_scores_gemma":[0.0004539561,0.0005781318,0.02441981,0.00007850515,0.00001774176,0.00003638904,0.0001896904,0.9731606,0.0007648817,0.00005531835,0.00003271613,0.0002122269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4475897,0.00005699995,0.5184228,0.00001818781,0.00005414729,0.0001040292,0.000001335963,0.00006800982,0.03368483],"genre_scores_gemma":[0.9907167,0.00004323904,0.008883926,0.0002142635,0.00004647937,0.000003072372,0.00000339347,0.000009804512,0.0000791041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9691066,"threshold_uncertainty_score":0.4770174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296874822674008,"score_gpt":0.2038087863902878,"score_spread":0.1808400381635478,"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."}}