{"id":"W4362502915","doi":"10.1007/978-3-031-29419-8_16","title":"Reinforcement Learning Aided Routing in Tactical Wireless Sensor Networks","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Wireless sensor network; Computer network; Network packet; Geographic routing; Routing protocol; Key distribution in wireless sensor networks; Dynamic Source Routing; Real-time computing; Wireless; Wireless network; Telecommunications","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002011122,0.0008565591,0.0009361511,0.001375702,0.0004113217,0.0007914175,0.003395591,0.0007259083,0.00001309359],"category_scores_gemma":[0.0002463274,0.0008628744,0.0002020274,0.001980071,0.0006156957,0.0005613228,0.002637707,0.003043331,0.00007369113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007572692,"about_ca_system_score_gemma":0.0003862185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007681592,"about_ca_topic_score_gemma":0.000191309,"domain_scores_codex":[0.9928717,0.0001400322,0.001161216,0.002407725,0.001649119,0.001770215],"domain_scores_gemma":[0.9956036,0.001823363,0.0005298024,0.001519357,0.0002292212,0.0002947171],"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":[0.000009802859,0.00001576655,0.000123001,0.00001637544,0.000009232355,0.0003855169,0.0003720749,0.86722,0.00002532433,0.02251386,0.000005971143,0.1093031],"study_design_scores_gemma":[0.0003909228,0.0001340154,0.0001369525,0.0009368638,0.00000647535,0.00005294082,7.955739e-7,0.9941545,0.0001520214,0.002981172,0.0001540296,0.0008993141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004447306,0.00007898905,0.9924236,0.000474045,0.002953831,0.0004249729,4.227904e-7,0.0005858119,0.002613598],"genre_scores_gemma":[0.9128615,0.0001465937,0.08327641,0.0009107526,0.001053592,0.00002021546,0.00001523033,0.0001397904,0.00157587],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9124168,"threshold_uncertainty_score":0.9993822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01696218349917092,"score_gpt":0.2395051527402027,"score_spread":0.2225429692410318,"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."}}