{"id":"W2902116167","doi":"10.3390/jlpea8040049","title":"Enhancing Reliability of Tactical MANETs by Improving Routing Decisions","year":2018,"lang":"en","type":"article","venue":"Journal of Low Power Electronics and Applications","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Federation for the Humanities and Social Sciences","keywords":"Computer science; Computer network; Dynamic Source Routing; Wireless Routing Protocol; Optimized Link State Routing Protocol; Destination-Sequenced Distance Vector routing; Ad hoc On-Demand Distance Vector Routing; Link-state routing protocol; Routing protocol; Zone Routing Protocol; Distributed computing; Routing (electronic design automation)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011209,0.0006732117,0.0003723108,0.0005643191,0.0003261048,0.0008419991,0.000825602,0.0004730746,0.0004960298],"category_scores_gemma":[0.005553511,0.000231901,0.0001883036,0.0004529471,0.0002873616,0.001050048,0.0006296503,0.0005096447,0.000245336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002733784,"about_ca_system_score_gemma":0.0004423743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005805143,"about_ca_topic_score_gemma":0.0007689258,"domain_scores_codex":[0.9993204,0.0002288486,0.00004418449,0.000102467,0.0002365518,0.0000675244],"domain_scores_gemma":[0.9969643,0.001409756,0.0005732371,0.0004197976,0.0005591387,0.00007379867],"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":[0.0002413828,0.0001364394,0.00503244,0.0002515486,0.0000853165,0.0002572292,0.0002859311,0.6893281,0.08015541,0.008481402,0.001128007,0.2146168],"study_design_scores_gemma":[0.00001899055,0.0004187325,0.001620247,0.00002533381,0.00006659298,0.0002093834,0.0001174338,0.9723029,0.01770947,0.004889999,0.002594156,0.0000268233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3376423,0.00231657,0.6493111,0.0005686025,0.0002272224,0.0001243792,0.0000806953,0.001035148,0.008694103],"genre_scores_gemma":[0.9687001,0.0006250512,0.02978926,0.00005132113,0.00005206786,0.00002832195,0.00004687356,0.0000253153,0.0006815064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001011209,"threshold_uncertainty_score":0.005347848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004376744065699563,"score_gpt":0.2452638750747167,"score_spread":0.2408871310090171,"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."}}