{"id":"W4318615361","doi":"10.11591/ijece.v13i3.pp2529-2545","title":"Research trends on microgrid systems: a bibliometric network analysis","year":2023,"lang":"en","type":"article","venue":"International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Positive Living North","funders":"","keywords":"Microgrid; Computer science; Scopus; Field (mathematics); Path (computing); Control (management); Computer network; Artificial intelligence","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00143813,0.0002427988,0.0005642568,0.02101176,0.00005639251,0.0005566511,0.0006348138,0.0001237102,0.000008197366],"category_scores_gemma":[0.00006135839,0.0002066725,0.000278094,0.009205244,0.00002624538,0.0003023269,0.00008509948,0.0007617419,0.000003238026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003303594,"about_ca_system_score_gemma":0.00007212814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007726721,"about_ca_topic_score_gemma":0.000001227443,"domain_scores_codex":[0.9968157,0.000097676,0.001073752,0.0001880821,0.001355977,0.0004688448],"domain_scores_gemma":[0.9970202,0.0004370607,0.0003897075,0.00009557589,0.001833673,0.000223729],"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":[0.000126609,0.00005493654,0.0008904798,0.00001459103,0.004202074,0.0002945035,0.00008415425,0.9623106,0.0004684724,0.002856205,0.003862895,0.02483449],"study_design_scores_gemma":[0.00127956,0.0007316229,0.007145627,0.000207518,0.0001566599,0.001157543,0.00002601031,0.9582115,0.0000558251,0.00007421667,0.03071556,0.0002383893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5154261,0.1293644,0.3366165,0.001111145,0.01665232,0.0003003712,0.00005294293,0.0001855622,0.0002905967],"genre_scores_gemma":[0.9822481,0.01487239,0.0004538144,0.00003012945,0.002317066,0.00000331663,0.00001014669,0.00003270349,0.00003227515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.466822,"threshold_uncertainty_score":0.9900842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008044825599781584,"score_gpt":0.2580307764672323,"score_spread":0.2499859508674507,"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."}}