{"id":"W4384929977","doi":"10.3390/en16145493","title":"A Systematic Heat Recovery Approach for Designing Integrated Heating, Cooling, and Ventilation Systems for Greenhouses","year":2023,"lang":"en","type":"article","venue":"Energies","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pinch analysis; Heat exchanger; Heat recovery ventilation; Greenhouse; Process engineering; Ventilation (architecture); Environmental science; Heat pump; Process integration; Thermal energy storage; Energy recovery; Passive cooling; Hybrid heat; Engineering; Waste heat; Mechanical engineering; Energy (signal processing); Heat transfer; Mathematics; Thermodynamics","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":[0.0006995001,0.001061006,0.0005430306,0.0008900117,0.0004045208,0.0005737104,0.0007681506,0.0004813287,0.001473873],"category_scores_gemma":[0.0007593293,0.000535537,0.0009506163,0.0003769789,0.0005195106,0.000501438,0.0004269542,0.0005155403,0.0002328701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004808295,"about_ca_system_score_gemma":0.001391931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001373562,"about_ca_topic_score_gemma":0.003323412,"domain_scores_codex":[0.9995551,0.0001334461,0.00002128467,0.00007374896,0.000180649,0.00003578398],"domain_scores_gemma":[0.9997618,0.000103406,0.00003786118,0.00003126395,0.00005872079,0.000006952379],"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":[0.00005304979,0.0001277666,0.0009753214,0.0007939606,0.00008443131,0.0001040797,0.0001750691,0.7851034,0.09150402,0.01080026,0.0004200534,0.1098586],"study_design_scores_gemma":[0.0000578299,0.001101973,0.002156669,0.0001180503,0.0001527313,0.0002479561,0.0001849971,0.9321724,0.04180167,0.008199025,0.01375538,0.00005130075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01387759,0.0001917755,0.9828987,0.00002273871,0.00000874768,0.0001752398,0.00003403259,0.0001918975,0.002599387],"genre_scores_gemma":[0.2494349,0.0003408077,0.7482285,0.00002447447,0.000008548798,0.0005954067,0.00009096153,0.00005644424,0.001219959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001473873,"threshold_uncertainty_score":0.004930615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743871054566015,"score_gpt":0.2269374642426079,"score_spread":0.1994987536969478,"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."}}