{"id":"W2160180223","doi":"10.1109/wimob.2008.17","title":"Accurately Predicting Residual Energy Levels in MANETs","year":2008,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Routing protocol; Optimized Link State Routing Protocol; Computer network; Link-state routing protocol; Metric (unit); Zone Routing Protocol; Dynamic Source Routing; Wireless Routing Protocol; Routing (electronic design automation); Residual; Distributed computing; Engineering; Algorithm","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":[0.0006285033,0.0004834738,0.0004319913,0.0005703217,0.0001838445,0.0005086513,0.0004494489,0.0004503115,0.0002007969],"category_scores_gemma":[0.002732242,0.0002434932,0.0001304073,0.0004470539,0.0002726247,0.001119875,0.0005272527,0.0003338127,0.0001758448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001741874,"about_ca_system_score_gemma":0.000174191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001212226,"about_ca_topic_score_gemma":0.001331669,"domain_scores_codex":[0.999716,0.00009302801,0.00002005436,0.00005022583,0.00009202772,0.00002866693],"domain_scores_gemma":[0.9989462,0.0004787644,0.0001849731,0.0002208707,0.0001360714,0.00003306575],"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":[0.0003190304,0.00007544927,0.01189512,0.00007554099,0.00005058998,0.0001440299,0.0001297694,0.8631761,0.02380785,0.00162821,0.0007092952,0.09798896],"study_design_scores_gemma":[0.000004699908,0.00007698269,0.002933132,0.000006095593,0.00001123821,0.00006543737,0.00004436705,0.9872904,0.00735169,0.001907436,0.0002918003,0.00001656394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6497723,0.000604278,0.346282,0.0001582704,0.00005202458,0.00002972738,0.0001677682,0.001161519,0.001771967],"genre_scores_gemma":[0.9809461,0.0001662979,0.01846798,0.00002053233,0.000008872378,0.000009926789,0.000118919,0.00001605023,0.0002452621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001212226,"threshold_uncertainty_score":0.003323853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05835062680358663,"score_gpt":0.2639265854424347,"score_spread":0.2055759586388481,"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."}}