{"id":"W4312440284","doi":"10.17762/ijcnis.v8i3.1420","title":"Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks","year":2022,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Information Security (IJCNIS)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Multipath routing; Wireless Routing Protocol; Cognitive radio; Dynamic Source Routing; Optimized Link State Routing Protocol; Zone Routing Protocol; Link-state routing protocol; Destination-Sequenced Distance Vector routing; Routing protocol; Robustness (evolution); Distributed computing; Routing (electronic design automation); 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":[0.0004594469,0.0005960927,0.0004782355,0.0006941768,0.0007209535,0.0007230541,0.0009987549,0.0005772892,0.0009854819],"category_scores_gemma":[0.001365503,0.0001798106,0.0004114777,0.0007762419,0.0003755097,0.000878209,0.000875014,0.0008228704,0.0002926172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006644432,"about_ca_system_score_gemma":0.0009665157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001458163,"about_ca_topic_score_gemma":0.002166966,"domain_scores_codex":[0.9995459,0.0001127473,0.00003258583,0.00007210823,0.0001728367,0.00006384366],"domain_scores_gemma":[0.9994754,0.0001754117,0.00008475457,0.00007153344,0.0001630809,0.00002985987],"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":[0.0004231413,0.0001456892,0.001213971,0.000819454,0.0002839528,0.001015558,0.0003563408,0.2113263,0.06326912,0.1057337,0.01800536,0.5974075],"study_design_scores_gemma":[0.0001078392,0.0006500459,0.001174753,0.0001357477,0.0002376412,0.001871973,0.0001966534,0.8171912,0.02541992,0.05641548,0.09640858,0.0001902274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02246769,0.008445841,0.9540863,0.0008890851,0.0007671867,0.0002664987,0.0001497102,0.00151028,0.01141756],"genre_scores_gemma":[0.7291664,0.007028405,0.2536274,0.0005598509,0.000316073,0.0005594821,0.0004546532,0.0001001179,0.008187766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001458163,"threshold_uncertainty_score":0.004820883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336365418015872,"score_gpt":0.2790407749086571,"score_spread":0.2656771207284984,"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."}}