{"id":"W2100403022","doi":"10.5555/1535571.1535583","title":"DTN based dominating set routing technique for mobile ad hoc networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Roaming; Computer science; Wireless ad hoc network; Distributed computing; Mobile ad hoc network; Adaptive quality of service multi-hop routing; Quality of service; Geographic routing; Delay-tolerant networking; Optimized Link State Routing Protocol; Node (physics); Routing protocol; Wireless network; Routing (electronic design automation); Wireless Routing Protocol; Wireless; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006393805,0.0001996173,0.0002544203,0.00006981202,0.000424734,0.00008529602,0.0006111974,0.000155221,0.00003461052],"category_scores_gemma":[0.00001253327,0.0001784579,0.000128118,0.0003145719,0.00006007682,0.000245024,0.0001642034,0.0001970689,0.000007301282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003944867,"about_ca_system_score_gemma":0.00013007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000436962,"about_ca_topic_score_gemma":0.000002852038,"domain_scores_codex":[0.9983873,0.00005026989,0.0003712437,0.0004635665,0.0002032785,0.0005243243],"domain_scores_gemma":[0.9985701,0.0004960574,0.0001454912,0.0005159286,0.000122934,0.0001494735],"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":[0.00007629742,0.0002260717,0.001071312,0.0000578849,0.00004223649,0.0002460595,0.000795854,0.01664619,0.0004301199,0.01058605,0.03619709,0.9336249],"study_design_scores_gemma":[0.0004553445,0.0001602357,0.00002490516,0.00003811656,0.000005391249,0.0000605845,0.00002909864,0.9918299,0.0004821893,0.0003167646,0.0063386,0.0002588601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008225871,0.0003140398,0.9932223,0.0001192868,0.000276576,0.0007697624,0.000003606925,0.0003756064,0.004096221],"genre_scores_gemma":[0.6803275,0.00003455776,0.3177969,0.000716334,0.0001292451,0.0002919901,0.00001358047,0.0000160108,0.000673919],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9751837,"threshold_uncertainty_score":0.7277303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03098235861945877,"score_gpt":0.260940381535487,"score_spread":0.2299580229160282,"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."}}