{"id":"W4388183399","doi":"10.36001/phmconf.2023.v15i1.3532","title":"Using Charge Determination Design of Experiments to Develop A Refrigerant Charge Health Status Model for Heat Pump Systems","year":2023,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Motors (Canada)","funders":"","keywords":"Refrigerant; Air source heat pumps; Heat pump; Condenser (optics); Coefficient of performance; Gas compressor; Intercooler; Heat exchanger; Hybrid heat; Superheating; Mechanical engineering; Water cooling; Thermodynamics; Nuclear engineering; Engineering; Process engineering; Automotive engineering","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":[0.004762094,0.001690707,0.0009937302,0.0006838894,0.0005386737,0.001059102,0.001460463,0.001763214,0.003211513],"category_scores_gemma":[0.006245951,0.0006587797,0.001846044,0.0002663633,0.0008026896,0.0009346705,0.0008193342,0.001722747,0.0004573905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634707,"about_ca_system_score_gemma":0.001303561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004399413,"about_ca_topic_score_gemma":0.002587764,"domain_scores_codex":[0.9983445,0.0005147927,0.0000975279,0.0004312745,0.0003944701,0.0002173973],"domain_scores_gemma":[0.9955979,0.002701341,0.0006696135,0.0002954693,0.0006547181,0.00008098313],"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":[0.0002308219,0.0003149277,0.00150969,0.0002247921,0.00004667919,0.00005504341,0.00006575192,0.9662024,0.01521169,0.002971919,0.0002115885,0.01295469],"study_design_scores_gemma":[0.00003449888,0.0006193892,0.0006687015,0.00001040565,0.00003144732,0.000009722063,0.00001326402,0.9899574,0.00684875,0.001204577,0.0005892449,0.00001258889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1196264,0.0003385936,0.8716487,0.0001915664,0.00007632729,0.001195179,0.0003530382,0.0007483526,0.005821881],"genre_scores_gemma":[0.876321,0.000235999,0.1162353,0.0001206995,0.00001993219,0.002596691,0.0002698759,0.00006191944,0.004138647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004762094,"threshold_uncertainty_score":0.02518469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1474736328745564,"score_gpt":0.3367796835041672,"score_spread":0.1893060506296108,"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."}}