{"id":"W2090945369","doi":"10.1109/wcnc.2012.6214247","title":"CSCD: A simple channel scan protocol to discover and join a cognitive PAN","year":2012,"lang":"en","type":"article","venue":"","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Piconet; Channel (broadcasting); Bluetooth; Simple (philosophy); Protocol (science); Computer science; Computer network; Event (particle physics); Real-time computing; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008382953,0.0003939654,0.0004888687,0.001176807,0.0008839685,0.00113424,0.001196256,0.0007035211,0.002981662],"category_scores_gemma":[0.001941214,0.000263947,0.0003077407,0.0006564161,0.001043115,0.001198863,0.002190344,0.0007462277,0.0007026356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004671519,"about_ca_system_score_gemma":0.001201442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00235798,"about_ca_topic_score_gemma":0.002851292,"domain_scores_codex":[0.9993882,0.0001074774,0.00005304714,0.00007331243,0.0002863269,0.00009162613],"domain_scores_gemma":[0.9987424,0.000369495,0.0001248798,0.0003336213,0.0002586094,0.0001709661],"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":[0.00154722,0.0005955037,0.005523171,0.001106486,0.0002032491,0.001689432,0.001601072,0.03322479,0.1913979,0.1122425,0.02432872,0.6265399],"study_design_scores_gemma":[0.0008214981,0.001990275,0.004448283,0.000135752,0.000272672,0.004058024,0.0006676003,0.5537466,0.1344076,0.03811648,0.2609268,0.0004083299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04721288,0.0006488117,0.9247715,0.0003529648,0.0003717773,0.001224019,0.0004200965,0.005301925,0.01969592],"genre_scores_gemma":[0.7434139,0.0005441784,0.2405312,0.0004006347,0.0001642529,0.001302385,0.0006766409,0.0002355282,0.01273129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002981662,"threshold_uncertainty_score":0.009974658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03050727827663511,"score_gpt":0.3029052566809294,"score_spread":0.2723979784042942,"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."}}