{"id":"W2974303744","doi":"10.1109/jiot.2019.2942037","title":"Energy Utilization-Aware Operation Control Algorithm in Energy Harvesting Base Stations","year":2019,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea; Korea University; National Research Foundation","keywords":"Energy consumption; Computer science; Base station; Energy (signal processing); Wireless sensor network; Transmission (telecommunications); Flexibility (engineering); Real-time computing; Computer network; Telecommunications; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003656676,0.000209064,0.0003014029,0.0003038545,0.00004158669,0.0001490735,0.0003023232,0.0001371516,0.000148756],"category_scores_gemma":[0.00005287574,0.0002191505,0.00008279047,0.0002104421,0.00003135128,0.0008799466,0.00002086705,0.0003918456,0.000006783793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001646314,"about_ca_system_score_gemma":0.00005539727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005539634,"about_ca_topic_score_gemma":0.0001365871,"domain_scores_codex":[0.9983858,0.0001062857,0.0007254301,0.0001816199,0.0002943051,0.000306538],"domain_scores_gemma":[0.9990991,0.0002187514,0.0002196747,0.0001684419,0.0001851169,0.0001089183],"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":[0.00000941052,0.00002982677,0.001395323,0.00002397288,0.00005980397,0.00002415838,0.0004230145,0.9574717,0.00427327,0.0008697572,0.0007884901,0.03463131],"study_design_scores_gemma":[0.0008113077,0.00005747609,0.0002217097,0.0004565941,0.00001330281,0.00009361995,0.00006176262,0.9848258,0.01183798,0.0002219458,0.001192331,0.0002061521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07695682,0.0003403046,0.9196904,0.00003859831,0.00168925,0.00004644017,0.000006122522,0.0001104323,0.001121646],"genre_scores_gemma":[0.9909846,0.0001351069,0.007508602,0.0001931271,0.0002450413,0.000009192966,0.00001903503,0.00006157585,0.0008436947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9140278,"threshold_uncertainty_score":0.89367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162660595399871,"score_gpt":0.2168712614160697,"score_spread":0.205244655462071,"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."}}