{"id":"W2393582145","doi":"10.1002/dac.3146","title":"The offloading model for green base stations in hybrid energy networks with multiple objectives","year":2016,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Base station; Base (topology); Computer network; Energy consumption; Distributed computing; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005785468,0.0001026028,0.0001442333,0.0001401029,0.00008798789,0.00008327559,0.0007347032,0.0000364175,6.658585e-7],"category_scores_gemma":[0.0001204034,0.00006317673,0.00005192442,0.00008216644,0.00005682883,0.0003410064,0.00003799332,0.000131888,3.664896e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002251277,"about_ca_system_score_gemma":0.00004665742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007013504,"about_ca_topic_score_gemma":0.0005122692,"domain_scores_codex":[0.9988819,0.0001122072,0.0005437348,0.00006705095,0.0002546276,0.0001404881],"domain_scores_gemma":[0.997003,0.001791212,0.0003071265,0.0002692589,0.0005843093,0.00004504488],"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":[0.00005999969,0.00001344803,0.001216672,0.000001885629,0.0001132509,0.00000173704,0.0001216846,0.9845397,0.0001536359,0.005044384,0.000299066,0.00843448],"study_design_scores_gemma":[0.0007943045,0.00001879953,0.0004325531,0.0004978628,0.000007077735,0.00003482923,0.00008110301,0.9947847,0.00009631603,0.0003791476,0.002786135,0.00008714741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01644109,0.001857359,0.9804034,0.0004598141,0.0004364073,0.00008922783,0.00001508187,0.00003558756,0.000261998],"genre_scores_gemma":[0.9955423,0.001100718,0.002867557,0.00001571835,0.000182002,0.00006314971,0.000006803738,0.00002996559,0.0001917522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9791012,"threshold_uncertainty_score":0.2576272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463846047788904,"score_gpt":0.2349744516533772,"score_spread":0.2203359911754882,"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."}}