{"id":"W4396214045","doi":"10.2316/j.2023.203-0500","title":"OPTIMAL REGULATION MODEL OF INTEGRATED ENERGY SYSTEM CONTAINING HYDROGEN STORAGE CONSIDERING ELECTROTHERMAL COUPLING, 1-8.","year":2023,"lang":"en","type":"article","venue":"International Journal of Power and Energy Systems","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coupling (piping); Hydrogen storage; Energy storage; Hydrogen; Energy (signal processing); Computer science; Materials science; Control theory (sociology); Chemistry; Physics; Thermodynamics; Control (management); Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005971253,0.001174938,0.001166189,0.0003973292,0.0006294777,0.001554617,0.001127766,0.001571807,0.0041732],"category_scores_gemma":[0.0006205409,0.0005338068,0.001047498,0.0004041652,0.0009204947,0.0007950762,0.0007316546,0.001140589,0.0004104319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190306,"about_ca_system_score_gemma":0.001469691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0217757,"about_ca_topic_score_gemma":0.01170159,"domain_scores_codex":[0.9997451,0.00005532574,0.000009465886,0.00006652753,0.00006879716,0.0000549284],"domain_scores_gemma":[0.9997563,0.00009504994,0.0000473543,0.00000962819,0.00007895909,0.00001270802],"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":[0.00005509369,0.000016664,0.0002067528,0.00006153406,0.00001922319,0.00006915459,0.00002845532,0.9938509,0.001573026,0.002309559,0.0002855644,0.001524035],"study_design_scores_gemma":[0.00001016574,0.00002612399,0.0001030353,0.000003689789,0.00001123033,0.000005598478,0.000007464263,0.9990371,0.0002338775,0.0003306084,0.0002280481,0.000003154094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1589575,0.00226736,0.7551273,0.001017241,0.000371927,0.0002778102,0.0008293667,0.00074905,0.08040252],"genre_scores_gemma":[0.9819407,0.0004955752,0.008630832,0.00005941372,0.00002306141,0.0002177155,0.0002082848,0.00003027757,0.008393962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0217757,"threshold_uncertainty_score":0.04329789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007999910644972361,"score_gpt":0.2026889546444027,"score_spread":0.1946890439994304,"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."}}