{"id":"W1968979245","doi":"10.1109/milcom.2013.229","title":"Efficient Broadcasting in Tactical Networks: The Impact of Local Topology Information Accuracy","year":2013,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada; Carleton University","funders":"","keywords":"Multicast; Computer science; Computer network; Broadcasting (networking); Flooding (psychology); Network topology; Network packet; Probabilistic logic; Distributed computing; Quality of service; Topology (electrical circuits); Multimedia Broadcast Multicast Service; 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":[0.003037723,0.0005372899,0.0007316118,0.0006955704,0.0005916576,0.00086418,0.0008260892,0.0007459966,0.0005605237],"category_scores_gemma":[0.02146232,0.0002503676,0.0001877521,0.0008769304,0.000717907,0.002987975,0.0008858176,0.0006027311,0.0001540215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007136977,"about_ca_system_score_gemma":0.0005836964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002771528,"about_ca_topic_score_gemma":0.003018397,"domain_scores_codex":[0.9977544,0.0009553512,0.00007727559,0.0001598152,0.0007616004,0.0002915002],"domain_scores_gemma":[0.982268,0.01446862,0.0009667722,0.001418047,0.0007416353,0.000136853],"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":[0.0005621429,0.0001541115,0.007412279,0.0003775906,0.00009044907,0.0002426265,0.0003326627,0.8279836,0.03767756,0.008465384,0.000912254,0.1157894],"study_design_scores_gemma":[0.00005236498,0.0006315715,0.004919972,0.00004269497,0.00008538722,0.000460465,0.000240358,0.9501175,0.03484154,0.006896445,0.001676783,0.00003504792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7472157,0.005581744,0.2384619,0.001095418,0.00007468614,0.00009903577,0.0001394958,0.0005843638,0.006747792],"genre_scores_gemma":[0.9813781,0.00116393,0.0168804,0.00003622362,0.00003280133,0.00001813048,0.00006056401,0.00003462159,0.0003952325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003037723,"threshold_uncertainty_score":0.01606518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009344962888489971,"score_gpt":0.2637070883183278,"score_spread":0.2543621254298379,"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."}}