{"id":"W2511807693","doi":"10.1021/acs.iecr.5b02616","title":"Modeling Vapor–Liquid–Liquid Phase Equilibria in Fischer–Tropsch Syncrude","year":2015,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Process Optimization and Integration","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Helmholtz-Alberta Initiative; Helmholtz-Gemeinschaft; University of Alberta; Natural Resources Canada; Syncrude","keywords":"Fischer–Tropsch process; Liquid phase; Liquid liquid; Phase (matter); Materials science; Chemistry; Thermodynamics; Catalysis; Chromatography; Physics; Organic chemistry; Selectivity","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":[0.0007498919,0.0005932658,0.0006020393,0.0004159987,0.0003717442,0.0006674213,0.0009332222,0.0009583465,0.0007581764],"category_scores_gemma":[0.0009641967,0.0005392444,0.0008375882,0.0005120929,0.000454915,0.0009438027,0.0005176994,0.001113313,0.0003813691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108884,"about_ca_system_score_gemma":0.001251258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01323719,"about_ca_topic_score_gemma":0.01141402,"domain_scores_codex":[0.9997818,0.00003686222,0.00001774704,0.00004981919,0.00008333889,0.00003045465],"domain_scores_gemma":[0.9996887,0.0001921947,0.00004153482,0.00002001762,0.0000513212,0.000006144022],"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":[0.00009168027,0.00007542421,0.002064339,0.0002443961,0.00003633767,0.0001400283,0.0001315957,0.9124922,0.06368491,0.01394059,0.000320671,0.006777819],"study_design_scores_gemma":[0.000007217353,0.00002786948,0.0001599138,0.000005331176,0.000005380814,0.000008903449,0.00001118941,0.9845814,0.01376604,0.0008436292,0.0005729182,0.00001021444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7204755,0.002007119,0.2656933,0.0003812739,0.00004710932,0.0002962398,0.001163375,0.0007832229,0.009152783],"genre_scores_gemma":[0.9487072,0.00131147,0.04616095,0.00008884807,0.00001244279,0.0003313742,0.0006788531,0.00009189345,0.002616992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01323719,"threshold_uncertainty_score":0.02632028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1782938969499311,"score_gpt":0.3676968699131216,"score_spread":0.1894029729631905,"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."}}