{"id":"W2588582300","doi":"10.1049/iet-wss.2018.5031","title":"Minimising number of sensors in wireless sensor networks for structure health monitoring systems","year":2018,"lang":"en","type":"article","venue":"IET Wireless Sensor Systems","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Qatar National Research Fund","keywords":"Wireless sensor network; Computer science; Structural health monitoring; Field (mathematics); Binary number; Genetic algorithm; Mathematical optimization; Wireless; Key distribution in wireless sensor networks; Distributed computing; Wireless network; Real-time computing; Computer network; Engineering; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00138079,0.0009595437,0.002031386,0.0005056653,0.0004987188,0.0005354962,0.001656652,0.000736589,0.000003946143],"category_scores_gemma":[0.00007053543,0.000957337,0.0003229537,0.001832397,0.0003463076,0.0005324192,0.0002961166,0.0006743154,0.00001721521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005854391,"about_ca_system_score_gemma":0.0002427968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001667712,"about_ca_topic_score_gemma":0.00009827304,"domain_scores_codex":[0.9914097,0.00101972,0.002451937,0.001780896,0.001207084,0.002130619],"domain_scores_gemma":[0.9938399,0.001024555,0.001658305,0.002019905,0.0009446295,0.0005126697],"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":[0.0001896784,0.0002631061,0.02520688,0.001485502,0.0002287173,0.00009451333,0.003238926,0.9450783,0.006555914,0.01317492,0.0009058737,0.003577681],"study_design_scores_gemma":[0.00161975,0.0002463631,0.0009499855,0.002376613,0.00002369314,0.0003347588,0.001678719,0.9871238,0.003777572,0.00001138971,0.0008297578,0.001027611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8170328,0.0008148389,0.1684567,0.0001638145,0.01099413,0.00175887,0.00007210977,0.0004661994,0.0002406148],"genre_scores_gemma":[0.9869378,0.000110239,0.009119492,0.00004980296,0.003039674,0.00009124541,0.00002634292,0.0001901659,0.0004352139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1699051,"threshold_uncertainty_score":0.9992877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01901964646063937,"score_gpt":0.2781771600643203,"score_spread":0.2591575136036809,"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."}}