{"id":"W2138758246","doi":"10.1109/glocom.2011.6134370","title":"A Novel Routing Algorithm in Cognitive Radio Ad Hoc Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Communications Research Centre Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Link-state routing protocol; Computer network; Dynamic Source Routing; Destination-Sequenced Distance Vector routing; Static routing; Wireless Routing Protocol; Multipath routing; Distributed computing; Policy-based routing; Optimized Link State Routing Protocol; Wireless ad hoc network; Adaptive quality of service multi-hop routing; Routing protocol; Routing (electronic design automation); Telecommunications; Wireless","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":[0.0003798175,0.0002010059,0.0002447055,0.0001435594,0.0001113779,0.0001123956,0.0003491958,0.00009001679,0.00004723677],"category_scores_gemma":[0.00003453937,0.0001896864,0.00008129793,0.000722226,0.00005660773,0.0004321307,0.0002113208,0.0003071794,0.00001684797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000610583,"about_ca_system_score_gemma":0.0000456457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001073819,"about_ca_topic_score_gemma":0.0002563499,"domain_scores_codex":[0.9983575,0.00005485314,0.0002908502,0.0005330521,0.0001736672,0.0005900878],"domain_scores_gemma":[0.9992805,0.0001930389,0.00008293871,0.0002363478,0.0000856587,0.0001215729],"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":[0.00001182513,0.0001176684,0.0005702549,0.000001055979,0.00002358917,0.0001343334,0.001866788,0.00004218179,0.00002648076,0.005520381,0.00004608362,0.9916394],"study_design_scores_gemma":[0.0009505986,0.0001003352,0.01925564,0.0001099395,0.000008024196,0.0001346683,0.0002244817,0.9779624,0.0001971962,0.0006198493,0.00009504185,0.0003418077],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005266102,0.00067886,0.9731973,0.00006765467,0.0003268369,0.0001861244,9.759144e-7,0.0001775919,0.02009859],"genre_scores_gemma":[0.8334216,0.0001197527,0.1656668,0.0004710214,0.0001348557,0.000005734562,0.000002087121,0.00001488842,0.0001632471],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9912975,"threshold_uncertainty_score":0.7735188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136123635008278,"score_gpt":0.2406452356984697,"score_spread":0.2092839993483869,"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."}}