{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003204634,0.0001225694,0.0002278614,0.00005397013,0.0001466368,0.00002920361,0.0002007545,0.00007885727,0.000003585458],"category_scores_gemma":[0.00007414443,0.0001012239,0.00007205184,0.0003507505,0.00003810621,0.0001509595,0.00005824407,0.00007094502,0.000003321614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000115922,"about_ca_system_score_gemma":0.0001852743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003172586,"about_ca_topic_score_gemma":0.000001187818,"domain_scores_codex":[0.99905,0.00003097689,0.0003236416,0.0001400407,0.0001771263,0.0002781823],"domain_scores_gemma":[0.999282,0.00004020215,0.00008386982,0.0002030818,0.0003471854,0.00004366802],"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":[0.00002908031,0.00007159972,0.000104432,0.0008918882,0.0001654715,2.951023e-7,0.07631984,0.4995652,0.4008712,0.005480102,0.01417706,0.002323803],"study_design_scores_gemma":[0.0001769609,0.00003974032,0.00003919985,0.0001374462,0.000004846624,4.38899e-7,0.001832622,0.9337192,0.06369184,0.0001553226,0.0001005972,0.0001018363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3266622,0.000083092,0.670898,0.000365198,0.000288601,0.0009889007,0.0003573086,0.0003265066,0.0000301564],"genre_scores_gemma":[0.9875965,0.00009373082,0.01191427,0.00004607792,0.00001281604,0.0001157783,0.00002379533,0.00001939537,0.0001776195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6609343,"threshold_uncertainty_score":0.4127791,"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."}}