{"id":"W4382653288","doi":"10.1002/9781119873747.ch4","title":"A Case Study and Detailed Implementation","year":2023,"lang":"en","type":"other","venue":"","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Python (programming language); Computer science; Hyperparameter; Reinforcement learning; Markov decision process; Artificial intelligence; Machine learning; Process (computing); Jamming; Wireless network; Deep learning; Wireless; Markov process; Programming language; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001722144,0.0005895894,0.0003293344,0.0005170834,0.00112569,0.00165463,0.001511842,0.001785679,0.02194202],"category_scores_gemma":[0.005404018,0.0002808976,0.0005240238,0.0006573805,0.0007804084,0.001668931,0.001786507,0.001364444,0.004204052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162671,"about_ca_system_score_gemma":0.001771706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006750001,"about_ca_topic_score_gemma":0.007759483,"domain_scores_codex":[0.9986058,0.0005447885,0.00007719724,0.0001633457,0.0003931827,0.0002157895],"domain_scores_gemma":[0.9983481,0.0007273384,0.00006572023,0.0002922121,0.0003490317,0.0002175999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"case_report","study_design_scores_codex":[0.0009856827,0.002251483,0.01367537,0.001262068,0.0001100755,0.01071744,0.002189894,0.2521816,0.01573575,0.1990846,0.1080541,0.393752],"study_design_scores_gemma":[0.0004451258,0.0008351034,0.00303738,0.0004004627,0.0000654131,0.003755787,0.002259886,0.5124624,0.02145653,0.06030057,0.394869,0.0001123784],"study_design_candidate":"case_report","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2065812,0.001107511,0.5434437,0.009524082,0.0007438834,0.002991967,0.00387659,0.009420531,0.2223106],"genre_scores_gemma":[0.5643109,0.0009675521,0.357892,0.001177559,0.00006827744,0.001481328,0.002198132,0.0008716597,0.07103258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02194202,"threshold_uncertainty_score":0.07340336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806594394701823,"score_gpt":0.3137732327603561,"score_spread":0.2857072888133379,"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."}}