{"id":"W4412454842","doi":"10.1016/j.enconman.2025.120183","title":"Novel hybridization concept for efficient performance of a peak-shaving technology by adsorption and liquid air energy storage systems","year":2025,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Balsillie School of International Affairs; University of Waterloo","funders":"","keywords":"Adsorption; Peaking power plant; Process engineering; Energy storage; Materials science; Liquid air; Environmental science; Engineering; Computer science; Chemistry; Physics; Electrical engineering; Renewable energy; Thermodynamics; Organic chemistry; Distributed generation","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":[],"consensus_categories":[],"category_scores_codex":[0.00006754098,0.0001111718,0.0001692911,0.0001864525,0.00006064026,0.00001035639,0.00006856107,0.00006077583,0.000002268432],"category_scores_gemma":[0.000001628236,0.000110338,0.00002659848,0.0001333498,0.00004055199,0.00003237689,0.00005080325,0.00002432359,1.736904e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003722243,"about_ca_system_score_gemma":0.000004375484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006290225,"about_ca_topic_score_gemma":0.00000166884,"domain_scores_codex":[0.9994459,0.000007440024,0.0001865915,0.0001622802,0.00007102841,0.0001268205],"domain_scores_gemma":[0.9997734,0.00001190543,0.00004568999,0.0001077898,0.00003391891,0.00002731709],"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":[0.0002570533,0.0001284896,0.00006034726,0.002746117,0.0005732124,0.000002006396,0.0002948743,0.7084956,0.05495846,0.2053541,0.007112488,0.0200173],"study_design_scores_gemma":[0.0007232924,0.00008658153,0.0000308973,0.0002135443,0.00007075351,0.000001605048,0.0006208361,0.9590139,0.004155971,0.000007208899,0.03494291,0.0001324496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1759244,0.003456828,0.818947,0.00004345257,0.0004785405,0.0001226221,0.00001062779,0.000106499,0.0009100797],"genre_scores_gemma":[0.9969862,0.001223148,0.00006764372,0.00003357642,0.00001398744,0.00003495492,0.00003199059,0.000009980036,0.001598484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8210618,"threshold_uncertainty_score":0.4499454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002551553980809766,"score_gpt":0.1771627099001953,"score_spread":0.1746111559193855,"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."}}