{"id":"W2136804526","doi":"10.1109/acc.2008.4586979","title":"A dual-network health state estimator and decision policy for unmanned combat teams","year":2008,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Estimator; Computer science; Scheme (mathematics); Dual (grammatical number); Wireless sensor network; Path (computing); Computer network; State (computer science); Wireless; Routing (electronic design automation); Motion planning; Operations research; Computer security; Engineering; Telecommunications; Artificial intelligence","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":[0.0005263022,0.0001989108,0.0003733395,0.0001077156,0.0004449098,0.0001474841,0.000424713,0.0000501167,0.000002406843],"category_scores_gemma":[0.0001165091,0.0001664147,0.00006939637,0.0004154499,0.0000519956,0.0003387046,0.0002056489,0.00007282083,0.00003788264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001297938,"about_ca_system_score_gemma":0.0003447959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005113996,"about_ca_topic_score_gemma":0.00008069586,"domain_scores_codex":[0.9980484,0.00006509155,0.000456355,0.0004882056,0.0002958533,0.0006460629],"domain_scores_gemma":[0.9984597,0.0003768437,0.0001734386,0.0005522792,0.00009881197,0.0003389046],"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":[0.0002048603,0.0003860454,0.007331239,0.0001439791,0.0001535658,0.00008157676,0.001666862,0.008502855,0.0001167814,0.2209502,0.2764044,0.4840577],"study_design_scores_gemma":[0.006414593,0.0007553798,0.01796181,0.0001557151,0.000006760464,0.0003111434,0.00004402946,0.9074884,0.00006748051,0.02402185,0.04212951,0.0006433036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01780614,0.0003431866,0.9769379,0.003178905,0.0003440556,0.0008576663,0.00003169892,0.0002993378,0.0002010669],"genre_scores_gemma":[0.7382708,0.00007909365,0.2588574,0.001752343,0.0002236772,0.00008836345,0.00001785452,0.00002355841,0.0006869013],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8989856,"threshold_uncertainty_score":0.6786196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735085752775423,"score_gpt":0.2844484579663578,"score_spread":0.2670976004386035,"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."}}