{"id":"W4411544858","doi":"10.1016/j.ijrefrig.2025.06.023","title":"A comprehensive variable refrigerant flow heat recovery model for building performance simulation","year":2025,"lang":"en","type":"article","venue":"International Journal of Refrigeration","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Hydro-Québec; Collège Shawinigan","funders":"Natural Sciences and Engineering Research Council of Canada; Trottier Institute for Sustainability in Engineering and Design; Hydro-Québec","keywords":"Refrigerant; Variable (mathematics); Computer science; Flow (mathematics); Environmental science; Process engineering; Mechanics; Heat exchanger; Engineering; Mechanical engineering; Mathematics; Physics","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":[0.000521189,0.001002777,0.001116927,0.0006376037,0.00066004,0.0009241666,0.002163594,0.001463116,0.005028869],"category_scores_gemma":[0.001093824,0.0006843996,0.001233398,0.0007715608,0.0004419022,0.0008077006,0.0007991955,0.001340103,0.0008440113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181481,"about_ca_system_score_gemma":0.001960972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04200124,"about_ca_topic_score_gemma":0.0256497,"domain_scores_codex":[0.9996662,0.00007221154,0.00001715483,0.00006774866,0.000117276,0.00005938832],"domain_scores_gemma":[0.999607,0.0001479441,0.00004085216,0.00003608303,0.0001368802,0.00003112697],"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":[0.000005726669,0.000008983423,0.0001966423,0.00001094089,0.000004485151,0.00001192473,0.000006564482,0.9978137,0.0002893319,0.0005051976,0.0001817908,0.0009646651],"study_design_scores_gemma":[0.000004258347,0.000006817264,0.0001627362,0.000002257045,0.000003227232,0.000004977386,0.000003537917,0.9989316,0.0001434134,0.0002060815,0.0005272834,0.000003776905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1742595,0.0007555934,0.7717822,0.0006314556,0.0001712602,0.0004007255,0.005236324,0.003219113,0.04354379],"genre_scores_gemma":[0.9176185,0.0004985395,0.06471591,0.0001174485,0.00005256765,0.0007551719,0.003268481,0.0003181793,0.01265513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04200124,"threshold_uncertainty_score":0.08351356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01561777183082399,"score_gpt":0.2791439384742724,"score_spread":0.2635261666434485,"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."}}