{"id":"W4311816559","doi":"10.1002/ese3.1371","title":"Natural gas‐fueled multigeneration for reducing environmental effects of brine and increasing product diversity: Thermodynamic and economic analyses","year":2022,"lang":"en","type":"article","venue":"Energy Science & Engineering","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Exergy; Brine; Environmental science; Waste management; Life-cycle assessment; Process engineering; Environmental engineering; Chemistry; 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":[0.0002909767,0.0002603309,0.0002320726,0.0007215717,0.0002465122,0.0004499746,0.0002827394,0.0002289468,0.002336149],"category_scores_gemma":[0.0002281146,0.0001016155,0.0003951958,0.0004529462,0.0002334666,0.0006277777,0.0002948152,0.0001652662,0.0001299346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008827422,"about_ca_system_score_gemma":0.0003089322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002461107,"about_ca_topic_score_gemma":0.003977975,"domain_scores_codex":[0.9998952,0.00001743935,0.000003482432,0.00001434325,0.00005212166,0.00001747154],"domain_scores_gemma":[0.9999155,0.00002678484,0.00001450694,0.000006736493,0.00002998668,0.000006450015],"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":[0.0008599746,0.0004211039,0.02165257,0.0006765408,0.0001340148,0.0007223799,0.00004407108,0.5607344,0.3103208,0.009247362,0.00124476,0.0939421],"study_design_scores_gemma":[0.00005914006,0.000748773,0.02775206,0.00003596157,0.0001034928,0.0001439366,0.0001748268,0.7692897,0.1926439,0.003689851,0.005323364,0.00003497806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738424,0.001245094,0.01561238,0.0001756991,0.00002141963,0.00005529451,0.0002750824,0.00004065134,0.008732013],"genre_scores_gemma":[0.9968671,0.0002301573,0.001807141,0.000005239327,0.000002320184,0.00001281207,0.00005115151,0.000005011512,0.001019066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002461107,"threshold_uncertainty_score":0.007815182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004102305242491288,"score_gpt":0.1917032449884454,"score_spread":0.1876009397459541,"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."}}