{"id":"W2108564948","doi":"10.1109/mobhoc.2007.4428634","title":"An Adaptive Delay-Minimized Route Design for Wireless Sensor-Actuator Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Actuator; Wireless sensor network; Computer science; Probabilistic logic; Key distribution in wireless sensor networks; Wireless; Scheduling (production processes); Real-time computing; Wireless network; Distributed computing; Energy consumption; Computer network; Engineering; Electrical engineering; Telecommunications; Artificial intelligence","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":[0.0007247775,0.0006764547,0.0004864884,0.0006145987,0.0005230193,0.0005600097,0.00127973,0.0003990556,0.0008504551],"category_scores_gemma":[0.00230829,0.0003245364,0.0003451967,0.000725829,0.0003535619,0.0009047652,0.0006262896,0.000421878,0.0002665279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005528484,"about_ca_system_score_gemma":0.0008700743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001408389,"about_ca_topic_score_gemma":0.002659078,"domain_scores_codex":[0.9994912,0.0001885497,0.00003489217,0.0001032982,0.000138714,0.00004329168],"domain_scores_gemma":[0.9993501,0.0002484268,0.0001175582,0.00008058149,0.0001646195,0.00003857668],"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":[0.0001699175,0.00004576857,0.0006181142,0.0001464346,0.00004598593,0.00005443546,0.0001033904,0.8068968,0.01173477,0.02310752,0.001664124,0.1554127],"study_design_scores_gemma":[0.00002360531,0.000125304,0.0001184228,0.000006366313,0.00001750605,0.00005451956,0.0000209529,0.9881167,0.003340349,0.004700965,0.003463327,0.00001195732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008459245,0.0001952338,0.9904193,0.00005252407,0.00003128869,0.00003507965,0.00002436171,0.0002265972,0.000556355],"genre_scores_gemma":[0.3971614,0.0005381915,0.5989729,0.00005020945,0.00004701876,0.000259112,0.000138882,0.0001137736,0.002718539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001408389,"threshold_uncertainty_score":0.004011214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02744561943128066,"score_gpt":0.2612103582534386,"score_spread":0.2337647388221579,"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."}}