{"id":"W2038343048","doi":"10.1587/transinf.e93.d.2306","title":"Hybrid Spatial Query Processing between a Server and a Wireless Sensor Network","year":2010,"lang":"en","type":"article","venue":"IEICE Transactions on Information and Systems","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Ministry of Land, Transport and Maritime Affairs","keywords":"Computer science; Wireless sensor network; Wireless network; Computer network; Key distribution in wireless sensor networks; Wireless WAN; Spatial query; Wireless; Transmission (telecommunications); Real-time computing; Web search query; Sargable; Search engine; Telecommunications; Information retrieval","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":[],"consensus_categories":[],"category_scores_codex":[0.000373046,0.0001799915,0.000216342,0.0001539606,0.0004506892,0.0006771322,0.0001951406,0.0001209282,0.000003639221],"category_scores_gemma":[0.000004597862,0.000165827,0.00003731949,0.0002381128,0.00006110367,0.001540031,0.00001014051,0.0003745831,0.00001694873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001947207,"about_ca_system_score_gemma":0.00004429678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002309074,"about_ca_topic_score_gemma":0.00006529417,"domain_scores_codex":[0.9986954,0.0000657128,0.0004487626,0.0002071409,0.0003010717,0.000281853],"domain_scores_gemma":[0.9991235,0.0001173846,0.000189053,0.0002894033,0.0001246541,0.0001560073],"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":[0.00004961073,0.00008261747,0.001478756,0.0005051384,0.00008469536,0.000008396929,0.004015835,0.3302907,0.0002552214,0.01119957,0.0002354434,0.651794],"study_design_scores_gemma":[0.0004878849,0.00005501585,0.00222131,0.0001273341,0.00001603649,0.000111727,0.0001525604,0.9903996,0.000192776,0.00001972261,0.005936921,0.0002790943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3017932,0.00002415224,0.6965699,0.0001913611,0.0006596858,0.0001857974,0.000006498983,0.000184025,0.0003854439],"genre_scores_gemma":[0.9976347,0.00002127113,0.001892084,0.0001488799,0.0001800806,0.00002890793,0.000007811706,0.000009004633,0.00007723434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6958416,"threshold_uncertainty_score":0.676223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00879889530598193,"score_gpt":0.2101749959989772,"score_spread":0.2013761006929953,"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."}}