{"id":"W2510290207","doi":"10.1021/acs.energyfuels.6b01419","title":"Prediction of Viscosity for Characterized Oils and Their Fractions Using the Expanded Fluid Model","year":2016,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Petrobras; Shell","keywords":"Asphaltene; Viscosity; Chemistry; Boiling point; Distillation; Thermodynamics; Fraction (chemistry); Mass fraction; Bubble point; API gravity; Mixing (physics); Chromatography; Vacuum distillation; Organic chemistry; Bubble; Petroleum","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":[0.0007450844,0.0009814107,0.0007093692,0.0009516848,0.0002027788,0.0004225872,0.0007471737,0.000510186,0.0005473744],"category_scores_gemma":[0.002327663,0.0003231027,0.0006950182,0.0006891963,0.0002604379,0.0009345795,0.0004073521,0.0007422553,0.0002771428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005908532,"about_ca_system_score_gemma":0.0008039706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003617498,"about_ca_topic_score_gemma":0.003158976,"domain_scores_codex":[0.9996744,0.00005658366,0.00001609248,0.00008444756,0.0001363005,0.00003217963],"domain_scores_gemma":[0.9994265,0.0002562597,0.0001129447,0.00007399038,0.0001108926,0.00001948371],"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":[0.0001871836,0.0001926635,0.00920341,0.0001606179,0.00007912907,0.0002108719,0.000128683,0.7463744,0.1790059,0.002462822,0.000284811,0.06170954],"study_design_scores_gemma":[0.000006743849,0.00005641146,0.001801357,0.000003872692,0.000009912002,0.00001787775,0.000007352415,0.9650226,0.03247329,0.0002947813,0.0002944675,0.000011477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3500504,0.0002123983,0.6471651,0.00003206003,0.00001251503,0.00009353152,0.0003437475,0.001093919,0.0009962576],"genre_scores_gemma":[0.8593113,0.0003753012,0.1377219,0.00001256251,0.000008308612,0.0002353712,0.0008284103,0.0001226112,0.001384355],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003617498,"threshold_uncertainty_score":0.00719285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02931999179483505,"score_gpt":0.2446494588088848,"score_spread":0.2153294670140498,"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."}}