{"id":"W2160331134","doi":"10.3390/s150717572","title":"Wireless Sensor Network Optimization: Multi-Objective Paradigm","year":2015,"lang":"en","type":"review","venue":"Sensors","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless sensor network; Optimization problem; Computer science; Software deployment; Key distribution in wireless sensor networks; Wireless network; Wireless; Distributed computing; Mathematical optimization; Computer network; Telecommunications; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005633479,0.001153493,0.002532793,0.0004100965,0.0003481208,0.0003096892,0.001640681,0.0006698832,0.00003074592],"category_scores_gemma":[0.0001897928,0.00105553,0.0005880664,0.002587549,0.0001963078,0.0005900934,0.0006132393,0.0008778241,0.0004485387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007632491,"about_ca_system_score_gemma":0.000806782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001153859,"about_ca_topic_score_gemma":0.00000443852,"domain_scores_codex":[0.9944378,0.0008859755,0.001113811,0.001790594,0.0007346869,0.00103715],"domain_scores_gemma":[0.9955641,0.0004378197,0.001094603,0.001773044,0.0006297685,0.0005006602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002762733,0.00007316317,4.113003e-7,0.0004548749,0.0001546101,0.0001056555,0.0002048338,0.6257678,6.752546e-9,0.000934087,0.0003681832,0.3719336],"study_design_scores_gemma":[0.0004321142,0.00004216462,3.322963e-7,0.001250293,0.0001415984,0.0002026401,0.00002221239,0.4774556,4.228068e-7,0.00007855416,0.5194396,0.0009344199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[3.240749e-8,0.4726758,0.5239341,0.00002538432,0.001154964,0.001036944,0.00002986889,0.0004877555,0.0006550932],"genre_scores_gemma":[1.157503e-7,0.5690269,0.4287076,0.00005379487,0.0004552764,0.0001034881,0.00008149396,0.000120717,0.001450601],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.5190714,"threshold_uncertainty_score":0.9991895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05381203925768556,"score_gpt":0.3300224179290673,"score_spread":0.2762103786713818,"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."}}