{"id":"W2946271479","doi":"10.1155/2019/1496208","title":"Efficient Aggregation Processing in the Presence of Duplicately Detected Objects in WSNs","year":2019,"lang":"en","type":"article","venue":"Journal of Sensors","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea; Ministry of Education; Ministry of Science, ICT and Future Planning; National Research Foundation","keywords":"Computer science","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":[0.003293784,0.000995533,0.001879256,0.001302752,0.001881439,0.001991415,0.002478768,0.0008932839,0.0004406756],"category_scores_gemma":[0.006863014,0.0006840279,0.0007887994,0.002453096,0.0008104336,0.003662546,0.002903058,0.0007823655,0.0003513947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000895341,"about_ca_system_score_gemma":0.001416955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002150123,"about_ca_topic_score_gemma":0.002000906,"domain_scores_codex":[0.9971172,0.0004579369,0.000402198,0.0007336891,0.001050406,0.0002385471],"domain_scores_gemma":[0.9938424,0.001785263,0.000646868,0.002444848,0.001094179,0.0001864282],"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":[0.002123411,0.0003698288,0.01303143,0.0008601324,0.0005120352,0.003420716,0.004771189,0.2043172,0.1946673,0.025527,0.01121551,0.5391843],"study_design_scores_gemma":[0.00007645284,0.0004511077,0.003092576,0.00004135176,0.0002643994,0.001812214,0.001308,0.8865904,0.07468023,0.02099713,0.01060422,0.00008202513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1767659,0.001792182,0.817199,0.0005331683,0.0002136962,0.0002174671,0.0003260434,0.001617702,0.001334929],"genre_scores_gemma":[0.6623222,0.0009291265,0.3322338,0.0003267284,0.000224317,0.0002022521,0.0009879969,0.000148024,0.002625552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003293784,"threshold_uncertainty_score":0.0174194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021267887296834,"score_gpt":0.2302532057393219,"score_spread":0.2200405268663536,"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."}}