{"id":"W4403684345","doi":"10.1016/j.enconman.2024.119170","title":"CO2 thermal network prototype: Identifying control parameters for optimal operation in transcritical mode","year":2024,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canetique (Canada); Natural Resources Canada","funders":"","keywords":"Transcritical cycle; Mode (computer interface); Thermal; Control theory (sociology); Control (management); Control engineering; Computer science; Environmental science; Engineering; Thermodynamics; Mechanical engineering; Physics; Artificial intelligence; Heat exchanger; Heat pump","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":[0.0004161008,0.0005952428,0.0003788737,0.0002799594,0.0006315317,0.0004984264,0.0009338274,0.0006554237,0.004269617],"category_scores_gemma":[0.0006443218,0.0001776418,0.0001727939,0.0001794879,0.0003493,0.0006056819,0.0003112814,0.0004295056,0.0005230064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005378015,"about_ca_system_score_gemma":0.0007167411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006111009,"about_ca_topic_score_gemma":0.007922482,"domain_scores_codex":[0.9998418,0.00003209521,0.000005878306,0.00004310382,0.00004547073,0.00003167703],"domain_scores_gemma":[0.9996634,0.0001026855,0.00002022979,0.00004028203,0.0001362365,0.00003723454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008034362,0.00185755,0.008718994,0.001024658,0.0001017774,0.0009171077,0.0009807717,0.3061504,0.567699,0.002948727,0.006226247,0.09534048],"study_design_scores_gemma":[0.0003811095,0.003728179,0.008502806,0.00002521697,0.00005528627,0.0001500333,0.0004647019,0.5371567,0.4424948,0.0007046529,0.006251658,0.0000848634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423953,0.00005581967,0.04169459,0.000204146,0.00007355539,0.0003402867,0.0003499216,0.0009450244,0.01394139],"genre_scores_gemma":[0.9938506,0.00001139537,0.003451205,0.00001481052,0.00000297679,0.0000894273,0.00006562044,0.00002975379,0.002484234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006111009,"threshold_uncertainty_score":0.01428336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009862616877466703,"score_gpt":0.2312229342960852,"score_spread":0.2213603174186185,"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."}}