{"id":"W2013219159","doi":"10.1002/wcm.408","title":"Localized energy efficient routing in mobile ad hoc networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Alberta","funders":"","keywords":"Computer science; Destination-Sequenced Distance Vector routing; Computer network; Link-state routing protocol; Dynamic Source Routing; Static routing; Geographic routing; Network packet; Distributed computing; Wireless Routing Protocol; Energy consumption; Routing protocol; Triangular routing; Policy-based routing; Equal-cost multi-path routing; Routing (electronic design automation); Electrical engineering; Engineering","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":[0.0005162735,0.0004953718,0.0006409232,0.000590389,0.0003803025,0.0009341252,0.0007154561,0.0007379094,0.001242806],"category_scores_gemma":[0.001567877,0.0002352444,0.0002436676,0.0008686438,0.0005310767,0.001402609,0.0006369317,0.0004910321,0.0005339223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003452147,"about_ca_system_score_gemma":0.0002353047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004045223,"about_ca_topic_score_gemma":0.0005221039,"domain_scores_codex":[0.9996077,0.0001838796,0.00001503948,0.00005033235,0.0001135896,0.00002952755],"domain_scores_gemma":[0.9995335,0.0002663085,0.00006022886,0.00005706619,0.0000645551,0.00001832121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001285957,0.00007824667,0.0007254514,0.0005117406,0.0001113715,0.0003625617,0.0002101496,0.669695,0.01374782,0.05504441,0.00845707,0.2509276],"study_design_scores_gemma":[0.00004561641,0.0002177676,0.000354598,0.00008283107,0.00005979701,0.0002977978,0.0001122036,0.915621,0.005693032,0.05271842,0.02476922,0.00002758484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03172206,0.008436171,0.9525336,0.0007703533,0.0002840292,0.00008610463,0.00004790498,0.0007575246,0.005362251],"genre_scores_gemma":[0.7706549,0.00815306,0.2111746,0.0003588345,0.0003757589,0.0001982949,0.0001769033,0.0000846016,0.008823092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001242806,"threshold_uncertainty_score":0.004157662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008655257954904306,"score_gpt":0.233423092319199,"score_spread":0.2247678343642947,"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."}}