{"id":"W1995704018","doi":"10.1109/tvt.2009.2024155","title":"An Adaptive Delay-Minimized Route Design for Wireless Sensor–Actuator Networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Wireless sensor network; Actuator; Scalability; Probabilistic logic; Computer science; Key distribution in wireless sensor networks; Wireless; Real-time computing; Distributed computing; Engineering; Wireless network; Computer network; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007739231,0.000844778,0.000476051,0.0006710658,0.0005500603,0.0006540964,0.0016788,0.0005312217,0.001353206],"category_scores_gemma":[0.002318922,0.0003514383,0.0004735164,0.0006804019,0.0004494748,0.001064133,0.0008096255,0.0005628365,0.0003606229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007264246,"about_ca_system_score_gemma":0.001046056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00222248,"about_ca_topic_score_gemma":0.003059204,"domain_scores_codex":[0.999466,0.0001660117,0.00003880551,0.0001239678,0.0001525507,0.00005266443],"domain_scores_gemma":[0.9993035,0.0002483043,0.0001168131,0.00009367499,0.0001955772,0.00004213393],"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":[0.000122062,0.00003636432,0.0004678214,0.0001257428,0.00003568832,0.00005934141,0.00008658011,0.8544838,0.01043509,0.01985661,0.00156184,0.112729],"study_design_scores_gemma":[0.00001802542,0.00009184897,0.00008071902,0.000006513182,0.00001115451,0.0000417203,0.00001504504,0.9901417,0.002633285,0.003775722,0.003173368,0.00001096895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008171252,0.00018546,0.9903349,0.00006356107,0.00003578711,0.00004196485,0.00003121598,0.0003418594,0.0007940189],"genre_scores_gemma":[0.3314346,0.0004847857,0.6644115,0.00006505918,0.00004268871,0.0002444931,0.0001808496,0.0001527889,0.00298333],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00222248,"threshold_uncertainty_score":0.00527066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589924103869642,"score_gpt":0.2393322567590801,"score_spread":0.2234330157203837,"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."}}