{"id":"W2067318858","doi":"10.3390/electronics3010001","title":"Compressed Air Energy Storage System Control and Performance Assessment Using Energy Harvested Index","year":2014,"lang":"en","type":"article","venue":"Electronics","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Compressed air energy storage; Energy storage; Renewable energy; Wind power; Energy (signal processing); Index (typography); Compressed air; Automotive engineering; Process engineering; Computer science; Engineering; Reliability engineering; Environmental science; Power (physics); Electrical engineering; Mechanical engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006356963,0.0005001685,0.0004204219,0.0004437623,0.0002274676,0.0008576163,0.0003620067,0.000237364,0.0007808294],"category_scores_gemma":[0.0009907471,0.00007530369,0.0002052539,0.0002747696,0.0004034508,0.0004846171,0.0002750566,0.0002739274,0.00009448946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004717712,"about_ca_system_score_gemma":0.0002141198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001670087,"about_ca_topic_score_gemma":0.001428694,"domain_scores_codex":[0.9995791,0.00007311263,0.00003171713,0.00005507411,0.0002329305,0.00002799321],"domain_scores_gemma":[0.9993597,0.0002882607,0.00009496677,0.0000433688,0.0001975006,0.00001628065],"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":[0.001398999,0.0002585951,0.007629961,0.0007138124,0.0001344602,0.0001467234,0.0002951875,0.6080098,0.1782025,0.009836864,0.00101752,0.1923556],"study_design_scores_gemma":[0.00001746516,0.0007448798,0.003107127,0.00002276086,0.00002894147,0.00005041017,0.00005904404,0.9337953,0.06034105,0.0007617838,0.001045506,0.00002563874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4234933,0.001182188,0.5615704,0.0001922021,0.00008766314,0.0001739439,0.0001505276,0.0005547458,0.01259507],"genre_scores_gemma":[0.9930243,0.00008328818,0.00627974,0.000007481709,0.000007457276,0.00002429021,0.00002673581,0.000009748165,0.000536981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001670087,"threshold_uncertainty_score":0.003422976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002926805550302088,"score_gpt":0.1726362889265179,"score_spread":0.1697094833762158,"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."}}