{"id":"W1997956955","doi":"10.1155/wcn/2006/74812","title":"Error Control Coding in Low-Power Wireless Sensor Networks: When Is ECC Energy-Efficient?","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":206,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Transmitter; Coding gain; Coding (social sciences); Wireless sensor network; Efficient energy use; Energy consumption; Energy harvesting; Decoding methods; Transmitter power output; Wireless; Implementation; Energy (signal processing); Real-time computing; Electronic engineering; Electrical engineering; Telecommunications; Computer network; Mathematics","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":[0.00138338,0.0003537135,0.0006918056,0.0005247103,0.0002766204,0.001159212,0.0006420457,0.000992859,0.001858066],"category_scores_gemma":[0.009025831,0.000199039,0.0001616894,0.0006683656,0.0009022634,0.003623289,0.0004091961,0.0006475559,0.0003498878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006133065,"about_ca_system_score_gemma":0.0004046898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000541505,"about_ca_topic_score_gemma":0.0009196119,"domain_scores_codex":[0.9991566,0.0002002664,0.000042626,0.00007988923,0.0004220445,0.00009863648],"domain_scores_gemma":[0.9940666,0.004137238,0.0003842138,0.0003776559,0.0009848985,0.00004944568],"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":[0.0006012588,0.0001604219,0.009533566,0.0009970091,0.000154254,0.0003632712,0.0003528364,0.2185196,0.06726968,0.1602952,0.002889452,0.5388635],"study_design_scores_gemma":[0.0001009033,0.0008350014,0.01035577,0.0008634723,0.0001987772,0.001613321,0.0006774818,0.591414,0.2125076,0.160335,0.02095988,0.0001387158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4187644,0.02530376,0.5214993,0.005862982,0.0003220729,0.00009953427,0.0001840966,0.0004457572,0.02751807],"genre_scores_gemma":[0.9434167,0.006293745,0.04636339,0.0002333545,0.0001201619,0.00004113639,0.00007451062,0.0000649814,0.003392108],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001858066,"threshold_uncertainty_score":0.007316113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01511021673447969,"score_gpt":0.2337337246119849,"score_spread":0.2186235078775052,"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."}}