{"id":"W2093498804","doi":"10.1109/infcomw.2014.6849184","title":"Energy Conserving Opportunistic Routing for self-powered wireless sensor networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer network; Wireless sensor network; Computer science; Routing protocol; Network packet; Energy consumption; Routing (electronic design automation); Survivability; Node (physics); Wireless Routing Protocol; Dynamic Source Routing; Engineering; Electrical engineering","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":[0.000580506,0.0003233662,0.0002789278,0.0003077114,0.0003972767,0.0004980554,0.0006869346,0.0002702425,0.0004997015],"category_scores_gemma":[0.001179734,0.0001649959,0.0002233889,0.0003804218,0.0002814742,0.0008074678,0.0005310397,0.0002941428,0.00009655997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002855868,"about_ca_system_score_gemma":0.0003761764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004125658,"about_ca_topic_score_gemma":0.001126602,"domain_scores_codex":[0.9997482,0.0000929816,0.00001570237,0.00002739505,0.0000889547,0.00002686588],"domain_scores_gemma":[0.9993466,0.0003764185,0.00008111939,0.000101033,0.00006826372,0.0000266291],"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":[0.000256515,0.0001978884,0.002461899,0.0005651389,0.0001473266,0.0007500915,0.0005064656,0.4453904,0.09358239,0.1119629,0.007200394,0.3369786],"study_design_scores_gemma":[0.00002572249,0.0001609015,0.0004570966,0.00003226206,0.00003369395,0.0004570181,0.00009050932,0.9438177,0.008556503,0.03322646,0.01311465,0.00002759236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06601191,0.002597114,0.9220508,0.0004492523,0.0001825812,0.0001340606,0.00008033637,0.0005764681,0.00791754],"genre_scores_gemma":[0.8650879,0.001843094,0.1273342,0.0001725692,0.000084851,0.0001768506,0.0001026148,0.00007681038,0.005121039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006869346,"threshold_uncertainty_score":0.003070056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009783135167313111,"score_gpt":0.1957999513557574,"score_spread":0.1860168161884443,"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."}}