{"id":"W2338096655","doi":"10.1021/acs.iecr.5b01780","title":"Extraction of EPA/DHA from 18/12EE Fish Oil Using AgNO<sub>3</sub>(aq): Composition, Yield, and Effects of Solvent Addition on Interfacial Tension and Flow Pattern in Mini-Fluidic Systems","year":2015,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Surface tension; Chemistry; Extraction (chemistry); Aqueous solution; Yield (engineering); Solvent; Silver nitrate; Fish oil; Hexane; Heptane; Raw material; Chromatography; Chemical engineering; Materials science; Organic chemistry; Thermodynamics; Fish <Actinopterygii>; Composite material; Fishery","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":[0.0002028206,0.0003009103,0.0002360253,0.0001527038,0.0001582226,0.0002465272,0.0001572477,0.0002486506,0.0004558988],"category_scores_gemma":[0.000315998,0.000173995,0.0001962217,0.0001315488,0.000175816,0.0003575036,0.0002452535,0.0003374019,0.0002705228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002091475,"about_ca_system_score_gemma":0.0001804372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007139556,"about_ca_topic_score_gemma":0.001591517,"domain_scores_codex":[0.9999055,0.00001240503,0.00001074258,0.00002724693,0.00002951706,0.00001454528],"domain_scores_gemma":[0.9998866,0.00004487272,0.00002632927,0.0000076089,0.00002339073,0.00001118055],"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":[0.00003162206,0.000003415872,0.00008583659,0.00001187025,0.000001580623,0.000006710647,0.000006824039,0.00004857455,0.9991713,0.00000979273,0.000005299737,0.0006174255],"study_design_scores_gemma":[0.000001764546,0.00003572391,0.0005804348,0.000001354139,0.000004097558,0.00001790069,0.000007174969,0.0007839103,0.9983245,0.00001117567,0.0002292919,0.00000276965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868037,0.0002786864,0.0118294,0.00004189625,0.0000110755,0.00002886829,0.0001891037,0.0001266323,0.0006906359],"genre_scores_gemma":[0.97213,0.0006938395,0.02478597,0.00004787982,0.00000815509,0.00006790936,0.0002882601,0.00005116807,0.001926886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007139556,"threshold_uncertainty_score":0.001525104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06136776087243757,"score_gpt":0.2750698576114271,"score_spread":0.2137020967389895,"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."}}