{"id":"W2084784494","doi":"10.1145/1795194.1795207","title":"Congestion control for spatio-temporal data in cyber-physical systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Network congestion; Granularity; Network packet; Cyber-physical system; Protocol (science); Data aggregator; Computer network; Physical layer; Data collection; Distributed computing; Real-time computing; Wireless sensor network; Wireless; Telecommunications; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003535597,0.00054983,0.0006407101,0.001200538,0.001277991,0.001695272,0.001563997,0.0006760136,0.0008938815],"category_scores_gemma":[0.01216311,0.0003353843,0.0004401069,0.0007419204,0.001475165,0.003181768,0.001554647,0.001022621,0.0001098275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610248,"about_ca_system_score_gemma":0.001461546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003494041,"about_ca_topic_score_gemma":0.003273225,"domain_scores_codex":[0.9982907,0.0005335371,0.0001712773,0.0002758717,0.000618203,0.000110412],"domain_scores_gemma":[0.9943302,0.003300649,0.0006518433,0.0006265939,0.0009108683,0.0001799713],"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":[0.00046335,0.0001708653,0.005124673,0.000503037,0.0001686896,0.000422472,0.001091697,0.5797931,0.03961352,0.176584,0.003742202,0.1923225],"study_design_scores_gemma":[0.00003822988,0.00008742065,0.0007066032,0.00002065892,0.00004085485,0.00006366656,0.00006700984,0.9722317,0.005278738,0.01798271,0.003450114,0.00003220224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03760964,0.0009803404,0.9586147,0.0005608554,0.0001862249,0.000113632,0.00004339434,0.0005414378,0.001349812],"genre_scores_gemma":[0.9190084,0.0006666008,0.07822283,0.0001203853,0.0001403803,0.000177722,0.00006313149,0.00006309814,0.001537496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003535597,"threshold_uncertainty_score":0.01869828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02010294885414594,"score_gpt":0.2633449698212936,"score_spread":0.2432420209671476,"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."}}