{"id":"W2546563341","doi":"10.1109/indcon.2013.6725884","title":"Energy and Congestion-Aware QoS routing for wireless sensor networks","year":2013,"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":"Concordia University","funders":"","keywords":"Computer network; Computer science; Quality of service; Wireless sensor network; Routing protocol; Scheduling (production processes); Network congestion; Distributed computing; Wireless Routing Protocol; Routing (electronic design automation); Engineering; Network packet","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":[0.0007993375,0.0004380427,0.0002623629,0.0003873487,0.0003861148,0.0006202745,0.0005868907,0.0004003799,0.0005142476],"category_scores_gemma":[0.001708128,0.0001626357,0.000235953,0.0005234303,0.0004056559,0.001083288,0.0004176538,0.0005567592,0.00009268873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000366743,"about_ca_system_score_gemma":0.0005818168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007340162,"about_ca_topic_score_gemma":0.0007755141,"domain_scores_codex":[0.9996655,0.0000980358,0.0000249735,0.00003340807,0.0001599335,0.00001814103],"domain_scores_gemma":[0.9994377,0.0002498502,0.00008548757,0.00006101445,0.0001400485,0.00002586734],"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":[0.0001826243,0.0001209132,0.002074116,0.001158871,0.0001299116,0.0004065539,0.0002899627,0.3433461,0.1310368,0.1297285,0.006021225,0.3855044],"study_design_scores_gemma":[0.00002594174,0.0002447322,0.0009303378,0.0000860474,0.00008130132,0.0005014161,0.00008916235,0.8974811,0.02722195,0.04233091,0.03094299,0.00006407025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0437601,0.01710964,0.9303663,0.001351496,0.0005457916,0.0001361353,0.00006685607,0.0006364517,0.006027131],"genre_scores_gemma":[0.7624479,0.01272281,0.219944,0.0002473011,0.0003841792,0.0001501092,0.0001292265,0.00008962761,0.003884925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007993375,"threshold_uncertainty_score":0.0042274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00904175000139033,"score_gpt":0.2042263745295171,"score_spread":0.1951846245281268,"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."}}