{"id":"W4403524711","doi":"10.1016/j.applthermaleng.2024.124667","title":"Techno-economic and advanced exergy analysis and machine-learning-based multi-objective optimization of the combined supercritical CO2 and organic flash cycles","year":2024,"lang":"en","type":"article","venue":"Applied Thermal Engineering","topic":"Phase Equilibria and Thermodynamics","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Supercritical fluid; Exergy; Process engineering; Flash (photography); Environmental science; Waste management; Industrial engineering; Computer science; Engineering; Thermodynamics; Physics","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":[0.0007596152,0.0005990872,0.0007006377,0.0009584521,0.0003096195,0.0009307336,0.0004233271,0.0006151877,0.0008458489],"category_scores_gemma":[0.0009747131,0.0003245132,0.0007903946,0.0006241493,0.0005211612,0.0005454835,0.0004558679,0.0004848364,0.00006641646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133728,"about_ca_system_score_gemma":0.001198945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01311353,"about_ca_topic_score_gemma":0.01230437,"domain_scores_codex":[0.9998382,0.00006394955,0.000007119587,0.00001560093,0.00004998487,0.00002515203],"domain_scores_gemma":[0.9996886,0.0002124887,0.00002264182,0.00001115118,0.00005283409,0.00001234024],"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":[0.00002463638,0.0000200595,0.0002481236,0.0000185334,0.00001469661,0.00001106349,0.000003654437,0.9957604,0.0005510363,0.0006961056,0.00003621694,0.002615537],"study_design_scores_gemma":[0.000001906511,0.000007936686,0.0002121624,9.354221e-7,0.000002977285,0.000001342267,0.000002978708,0.9991221,0.0003670581,0.0002394142,0.00003961816,0.00000154036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8563418,0.001222624,0.1301868,0.0003816007,0.00005059875,0.00008892138,0.0002866287,0.00008069265,0.01136039],"genre_scores_gemma":[0.9934636,0.0001390771,0.00447711,0.00001327301,0.000009938401,0.00003630532,0.00006898039,0.00001380863,0.001777835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01311353,"threshold_uncertainty_score":0.02607441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002818413627932171,"score_gpt":0.1747298885429722,"score_spread":0.17191147491504,"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."}}