{"id":"W4307405434","doi":"10.1002/cjce.24725","title":"Liquid–liquid equilibria of ternary mixtures of methanol +  <scp>MEG</scp>  +  <scp> <i>n</i> ‐C5 </scp> , ethanol +  <scp>MEG</scp>  +  <scp> <i>n</i> ‐C5 </scp> , and <scp> <i>n</i> ‐butanol </scp>  +  <scp>MEG</scp>  +  <scp> <i>n</i> ‐C5 </scp>","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Phase Equilibria and Thermodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Petrobras; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Ethylene glycol; Ternary operation; Binodal; Solubility; Chemistry; Methanol; Pentane; Ternary numeral system; Titration; Ethanol; Analytical Chemistry (journal); Thermodynamics; Chromatography; Organic chemistry; Phase (matter); Phase diagram; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003438114,0.0002738527,0.0003520467,0.0006579505,0.0004407508,0.0003736524,0.0004448655,0.0002409236,0.002566516],"category_scores_gemma":[0.0008636761,0.00017479,0.0002549721,0.0005777265,0.0004175551,0.0005583413,0.0002776281,0.0006484659,0.0004404467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001023543,"about_ca_system_score_gemma":0.0005324741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005609127,"about_ca_topic_score_gemma":0.00675214,"domain_scores_codex":[0.9997333,0.00003884492,0.0000205919,0.00005380128,0.0001049651,0.00004850926],"domain_scores_gemma":[0.9997218,0.0001358843,0.00004205821,0.0000112681,0.00006662014,0.00002226457],"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":[0.0005707567,0.00008131724,0.001223602,0.0001746674,0.000032023,0.0001200837,0.0002150358,0.00213359,0.9886249,0.00101127,0.0002789894,0.005533764],"study_design_scores_gemma":[0.00001601713,0.0001195948,0.002257586,0.000008714384,0.00001533571,0.00003056289,0.0000616293,0.00927964,0.9871507,0.0001481125,0.0008979185,0.00001419307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905838,0.0006275194,0.003447267,0.00008009133,0.0000275807,0.00003375537,0.0008255973,0.0001195161,0.004254894],"genre_scores_gemma":[0.9962993,0.0003056486,0.001564573,0.00002293383,0.000008559333,0.00004046389,0.0005483532,0.00002847196,0.001181722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005609127,"threshold_uncertainty_score":0.01115292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00815573839108066,"score_gpt":0.1970031203604238,"score_spread":0.1888473819693431,"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."}}