{"id":"W2029271328","doi":"10.1109/sege.2013.6707898","title":"Research and development of a microgrid control and monitoring system for the remote community of Bella Coola: Challenges, solutions, achievements and lessons learned","year":2013,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Research Council Canada; BC Hydro; Government of Canada","keywords":"BELLA; Microgrid; Smart grid; Renewable energy; Computer security; Control (management); Engineering; Computer science; Environmental economics; Architectural engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009608592,0.0000856506,0.000176584,0.00006390114,0.000335132,0.00002838959,0.00008483043,0.0000540571,0.00000104834],"category_scores_gemma":[0.00002021293,0.0000646261,0.00001113721,0.00004895217,0.0000800466,0.00005907162,0.00008276568,0.0001492646,3.69233e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002612424,"about_ca_system_score_gemma":0.0000143839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003069031,"about_ca_topic_score_gemma":0.00009196648,"domain_scores_codex":[0.9993168,0.00008356741,0.0002285173,0.00008600877,0.00009561177,0.0001895521],"domain_scores_gemma":[0.9992267,0.0003737358,0.00003722655,0.0001487638,0.000170368,0.00004317442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001109379,0.00008541563,0.001419231,0.002555048,0.0006008342,1.920116e-7,0.005004215,0.001676109,0.1054307,0.0008249894,0.0001203905,0.8821719],"study_design_scores_gemma":[0.01635958,0.0007401627,0.1532703,0.001721994,0.0002435071,0.00002624584,0.07317575,0.6928068,0.05418622,0.0004831439,0.006057571,0.0009286241],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.876087,0.081751,0.03869503,0.001020035,0.0001264959,0.001988616,0.00002773151,0.00009032185,0.0002137531],"genre_scores_gemma":[0.9872431,0.006890592,0.005778782,0.000001736542,0.00001719444,0.00003957267,0.000002323223,0.00001167492,0.00001502789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8812433,"threshold_uncertainty_score":0.2635376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1351456725419637,"score_gpt":0.3111301475870207,"score_spread":0.175984475045057,"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."}}