{"id":"W4391402944","doi":"10.22541/au.170670861.16240534/v1","title":"Computational Analysis of Citric Acid Pertraction in Emulsion Liquid Membranes","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Emulsion; Sizing; Citric acid; Membrane; Process engineering; Process (computing); Work (physics); Chemistry; Computer science; Particle (ecology); Chromatography; Materials science; Engineering; Mechanical engineering; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005134091,0.000654999,0.001290669,0.0006369581,0.001050256,0.001221914,0.0009819996,0.002198288,0.002481155],"category_scores_gemma":[0.001707811,0.0004696766,0.001191165,0.0006756797,0.0008370465,0.0006213215,0.0008089287,0.0009295904,0.0002000516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073167,"about_ca_system_score_gemma":0.001646771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0206756,"about_ca_topic_score_gemma":0.009367485,"domain_scores_codex":[0.9998094,0.00005033108,0.00001020562,0.00002869314,0.00004726617,0.00005400031],"domain_scores_gemma":[0.9989807,0.0007268348,0.00006380044,0.00004014817,0.0001255301,0.00006296641],"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":[0.00008533669,0.00006346239,0.0009786652,0.00006738781,0.00002152168,0.0001426907,0.00002312428,0.994759,0.0008916676,0.00152448,0.0002317874,0.001210789],"study_design_scores_gemma":[0.00001141201,0.00001676498,0.0001930257,0.000003650802,0.000004442117,0.000007418811,0.00001435029,0.9990958,0.0002704833,0.0002564123,0.0001227111,0.000003456717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9478634,0.001071731,0.02890646,0.001225764,0.0001284527,0.0001147486,0.001133551,0.0002104305,0.01934536],"genre_scores_gemma":[0.9833014,0.0003449696,0.01223928,0.0001549224,0.0000302494,0.0001742836,0.0005774383,0.00007118803,0.003106319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0206756,"threshold_uncertainty_score":0.04111052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559180595830131,"score_gpt":0.2807647743447867,"score_spread":0.2651729683864854,"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."}}