{"id":"W4206739815","doi":"10.1109/access.2021.3138990","title":"Microgrid Digital Twins: Concepts, Applications, and Future Trends","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada)","funders":"Villum Fonden","keywords":"Microgrid; Computer science; Data science; Artificial intelligence; Control (management)","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":[0.001077029,0.00060368,0.0003878984,0.001704142,0.0007129065,0.003526841,0.001216529,0.001196941,0.006578282],"category_scores_gemma":[0.001263188,0.000297815,0.0004391418,0.003129846,0.001910387,0.007108662,0.002616249,0.001575443,0.001492481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548177,"about_ca_system_score_gemma":0.001099848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001164961,"about_ca_topic_score_gemma":0.001321967,"domain_scores_codex":[0.9995282,0.00009766719,0.00003998915,0.00008938647,0.0001895294,0.00005518681],"domain_scores_gemma":[0.9991674,0.000233885,0.00007936073,0.00009465493,0.0002814052,0.000143232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006658609,0.00006841515,0.001571423,0.001560845,0.00002216559,0.0003397894,0.0006979909,0.004242849,0.003151855,0.4480865,0.01614373,0.5240477],"study_design_scores_gemma":[0.00001067318,0.0002446442,0.001281736,0.000969107,0.00003321056,0.001756593,0.001699607,0.01141774,0.003348961,0.1270892,0.8520876,0.00006097811],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03307931,0.4865045,0.2096122,0.02090658,0.004053316,0.0002087021,0.0003547096,0.001285191,0.2439956],"genre_scores_gemma":[0.3315585,0.4889615,0.1231415,0.004436887,0.002974362,0.0002207353,0.0006745878,0.000312143,0.04771986],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006578282,"threshold_uncertainty_score":0.02200657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532145901473052,"score_gpt":0.2731486851798444,"score_spread":0.2578272261651139,"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."}}