{"id":"W4390277174","doi":"10.1016/j.jobe.2023.108407","title":"Modeling and optimization of two-stage compression heat pump system for cold climate applications","year":2023,"lang":"en","type":"article","venue":"Journal of Building Engineering","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"Office of Energy Research and Development; Natural Resources Canada","keywords":"Coefficient of performance; Air source heat pumps; Heat pump; Condenser (optics); Gas compressor; Evaporator; Vapor-compression refrigeration; Refrigerant; Economizer; Hybrid heat; Materials science; Discharge pressure; Heat exchanger; Thermodynamics; Compression ratio; Nuclear engineering; Mechanics; Mechanical engineering; Engineering","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":[0.0002746075,0.0006963534,0.001179498,0.0004220471,0.0009305732,0.001202859,0.0009598361,0.001187071,0.005081247],"category_scores_gemma":[0.0004234062,0.0006859939,0.0008749957,0.0004126874,0.0004759621,0.0007105211,0.0004840137,0.0005497374,0.0004041175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001106922,"about_ca_system_score_gemma":0.001675915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02291248,"about_ca_topic_score_gemma":0.01594836,"domain_scores_codex":[0.9998271,0.00003380983,0.000005960599,0.00003187266,0.00005250499,0.00004870908],"domain_scores_gemma":[0.9998314,0.00007872321,0.00001923394,0.000009316727,0.0000459773,0.00001527301],"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":[0.00003567694,0.0000269307,0.0002994578,0.00003092786,0.000009291472,0.00003341319,0.00001032068,0.9957091,0.001629245,0.0004345006,0.0001825478,0.001598598],"study_design_scores_gemma":[0.000006669883,0.00002208101,0.0001880356,0.000001161258,0.000005006179,0.000004625118,0.000005384515,0.9991825,0.0003763583,0.00006617855,0.0001389939,0.000002831344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6555865,0.00176397,0.2698627,0.0008418968,0.0002421545,0.0003389618,0.0009473765,0.0008585648,0.06955786],"genre_scores_gemma":[0.9894035,0.0002041429,0.003941209,0.00002124582,0.0000133568,0.00008627194,0.00008871339,0.00003560958,0.006206126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02291248,"threshold_uncertainty_score":0.04555821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01413720911671425,"score_gpt":0.2478166246515443,"score_spread":0.2336794155348301,"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."}}