{"id":"W2398437049","doi":"10.1016/j.adhoc.2016.04.012","title":"Efficient and robust serial query processing approach for large-scale wireless sensor networks","year":2016,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Wireless sensor network; Scale (ratio); Wireless; Distributed computing; Computer network; Telecommunications; Geography; Cartography","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":[0.0009590465,0.0005811637,0.0006329398,0.0001422376,0.0006778473,0.000418927,0.001000874,0.0005116895,0.000005350186],"category_scores_gemma":[0.00002952426,0.0004417014,0.000192711,0.0007183282,0.0002013072,0.0003061484,0.0005818196,0.0003751786,0.000003622499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001210954,"about_ca_system_score_gemma":0.00007665429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002801339,"about_ca_topic_score_gemma":0.00002427502,"domain_scores_codex":[0.9955211,0.0002012774,0.000650591,0.001511952,0.0004492707,0.001665764],"domain_scores_gemma":[0.9975262,0.000481291,0.0003571805,0.0009815223,0.0002541866,0.000399637],"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":[0.0001083447,0.0001740659,0.0001766131,0.00003245997,0.00002832362,0.000008350044,0.0002090203,0.9022629,0.00008082682,0.001884321,0.0007745583,0.09426026],"study_design_scores_gemma":[0.001896653,0.0001280453,0.0002075049,0.0002011796,0.00003316871,0.00004522456,0.00007426233,0.9947855,0.00005748303,0.00002499122,0.001860249,0.0006856954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03952055,0.003771032,0.9535431,0.0003286752,0.001219118,0.0007336321,0.000008260442,0.0005699627,0.0003056322],"genre_scores_gemma":[0.8072831,0.0004880235,0.189217,0.00042161,0.001638841,0.0001952216,0.00002778865,0.0001210614,0.0006074089],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7677625,"threshold_uncertainty_score":0.9998035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137567256663774,"score_gpt":0.2114434253514631,"score_spread":0.2000677527848253,"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."}}