{"id":"W2982480115","doi":"10.1109/wcnc.2019.8886159","title":"Bounds on Path Exposure in Energy Harvesting Wireless Sensor Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Wireless sensor network; Computer science; Probabilistic logic; Node (physics); Path (computing); Wireless; Computer network; Energy (signal processing); Energy harvesting; Intrusion detection system; Transmission (telecommunications); Wireless network; Intrusion; Range (aeronautics); State (computer science); Key distribution in wireless sensor networks; Power (physics); Real-time computing; Algorithm; Telecommunications; Engineering; Mathematics; Computer security","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"],"consensus_categories":[],"category_scores_codex":[0.0002171056,0.0003366915,0.0003486119,0.0001434045,0.00004666808,0.0001021122,0.0002549998,0.0002807149,0.0000997353],"category_scores_gemma":[0.00002130452,0.0003377441,0.00006841515,0.0004261025,0.00002959183,0.0001825146,0.00005180163,0.00047959,0.00006179576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303711,"about_ca_system_score_gemma":0.00001616196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002184257,"about_ca_topic_score_gemma":0.0004188656,"domain_scores_codex":[0.9982432,0.00006618778,0.0004126353,0.0003836963,0.0002293468,0.0006648964],"domain_scores_gemma":[0.9990284,0.0002895938,0.00004104554,0.0004878759,0.00003033532,0.0001227105],"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":[0.000008062986,0.00002193377,0.01566729,0.0000274748,0.00001696288,0.0000325427,0.00003779873,0.9674285,0.0005717569,0.004749591,0.0004107844,0.01102729],"study_design_scores_gemma":[0.0004798709,0.00007074019,0.006635219,0.0003061469,0.000003971088,0.00001010772,0.00003909267,0.9884111,0.0005432233,0.00002605237,0.003025533,0.0004488932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9268413,0.0002939277,0.01743134,0.0000216968,0.001260987,0.0001029811,0.000001469915,0.0009912561,0.05305508],"genre_scores_gemma":[0.9937382,0.0001077169,0.001324274,0.0002289824,0.0003710433,0.00002731054,0.00002013308,0.0001274927,0.004054791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06689699,"threshold_uncertainty_score":0.9999074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005474424900253281,"score_gpt":0.1779553803116079,"score_spread":0.1724809554113546,"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."}}