{"id":"W2082136964","doi":"10.1021/ef900150p","title":"Measurement and Modeling of Asphaltene Precipitation from Crude Oil Blends","year":2009,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Schlumberger (Canada); University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Asphaltene; Heptane; Fraction (chemistry); Toluene; Mass fraction; Molar mass; Chemistry; Yield (engineering); Crude oil; Precipitation; Light crude oil; Thermodynamics; Chromatography; Analytical Chemistry (journal); Materials science; Organic chemistry; Polymer; Composite material; Petroleum engineering","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":[0.0003105021,0.0006921785,0.0005577894,0.000502341,0.0002184363,0.0004386159,0.0006642409,0.0006208032,0.0003281504],"category_scores_gemma":[0.000716694,0.0003361358,0.000563562,0.0004856701,0.0001904317,0.0006365697,0.0003309803,0.0004757362,0.0002978256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006575374,"about_ca_system_score_gemma":0.0003997381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004548244,"about_ca_topic_score_gemma":0.002840402,"domain_scores_codex":[0.9997844,0.00002093193,0.00001487981,0.00005897473,0.00009803606,0.00002270775],"domain_scores_gemma":[0.999774,0.00006645281,0.00003816846,0.00003570976,0.00007149055,0.00001421146],"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":[0.000152116,0.0001444693,0.005895491,0.0001067412,0.00003661511,0.0001714782,0.00006044739,0.6290165,0.3476132,0.0005491864,0.0001035055,0.01615037],"study_design_scores_gemma":[0.000004555102,0.0000305705,0.0006227999,7.579566e-7,0.000003614702,0.00001327724,0.000004262679,0.9510219,0.04810394,0.0000658059,0.0001233809,0.000005212712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7472968,0.0002067386,0.2495037,0.00003274969,0.00001451734,0.0001091562,0.0004028114,0.0008759199,0.0015576],"genre_scores_gemma":[0.9611712,0.0002233053,0.03692345,0.000009687293,0.000003535436,0.00009306345,0.0003330311,0.00008351228,0.00115926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004548244,"threshold_uncertainty_score":0.009043574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02184682075251977,"score_gpt":0.2381651394691398,"score_spread":0.2163183187166201,"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."}}