{"id":"W2147036035","doi":"10.1002/wcm.809","title":"Cognitive wireless personal area network for monitoring and control","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Network packet; Node (physics); Wireless; ISM band; Transmission (telecommunications); Frequency-hopping spread spectrum; Cognitive radio; Duration (music); Real-time computing; Personal area network; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004092341,0.0002021068,0.000310674,0.00006405995,0.001193777,0.0003193886,0.0004360199,0.00007061112,4.297773e-7],"category_scores_gemma":[0.00001724413,0.000209704,0.00006674344,0.0002391019,0.0001451898,0.0002103287,0.0002841108,0.0002448464,4.226866e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002906339,"about_ca_system_score_gemma":0.00003501836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000130346,"about_ca_topic_score_gemma":0.000006373748,"domain_scores_codex":[0.9986724,0.0001153161,0.0002820438,0.0004001939,0.0001147463,0.0004153131],"domain_scores_gemma":[0.997827,0.001259649,0.0001491229,0.0004398512,0.0001957633,0.0001286039],"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":[0.00001577194,0.00006590944,0.002786527,0.00001080641,0.00004119876,0.000002370138,0.001598229,0.0001610266,0.0004185246,0.009679513,0.00002371631,0.9851964],"study_design_scores_gemma":[0.00104729,0.0002126853,0.008333252,0.0003566587,0.0000316734,0.00004835387,0.0004226236,0.987767,0.00007667622,0.0009320781,0.0004860938,0.0002856245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4194062,0.004496258,0.5746642,0.0005244598,0.0001027574,0.0004751912,0.000005777156,0.0001213111,0.0002037966],"genre_scores_gemma":[0.9803729,0.000918771,0.01818552,0.0002162745,0.0002456702,0.00002973557,0.000009095659,0.00001242715,0.000009604647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.987606,"threshold_uncertainty_score":0.9181687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182102416612557,"score_gpt":0.2764652369682792,"score_spread":0.2546442128021537,"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."}}