{"id":"W4405384956","doi":"10.1002/cjce.25583","title":"Optimization of process parameters in supercritical <scp>CO<sub>2</sub></scp> extraction of rose essential oil: Evaluation of phenolic, flavonoid, and antioxidant profiles","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Essential Oils and Antimicrobial Activity","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Supercritical fluid; Flavonoid; Solubility; Essential oil; Chromatography; Yield (engineering); Chemistry; Supercritical fluid extraction; Antioxidant; Response surface methodology; Supercritical carbon dioxide; Volumetric flow rate; Materials science; Organic chemistry; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004318783,0.00008234811,0.000190811,0.00005492547,0.00002123624,0.00003040151,0.00009547855,0.00009200776,0.000005748729],"category_scores_gemma":[0.0002952629,0.00004057525,0.00006723386,0.0002446491,0.00009344294,0.0001885401,0.00000720181,0.0002109721,1.040791e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003876577,"about_ca_system_score_gemma":0.00009558285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004788091,"about_ca_topic_score_gemma":0.000230023,"domain_scores_codex":[0.9991967,0.00003617571,0.0003291714,0.00008934708,0.0002063627,0.0001422416],"domain_scores_gemma":[0.9994559,0.00019146,0.00006311537,0.00002427025,0.0001716078,0.00009359061],"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":[0.000005027747,0.00002187266,0.00008296077,0.000129275,0.00001554919,0.000002650564,0.0001521898,0.02683031,0.9699922,0.00004442882,0.000005520199,0.002717969],"study_design_scores_gemma":[0.00009206957,0.00003553715,0.0007202478,0.0002879061,0.00004578409,0.0000241281,0.00005194043,0.03760689,0.9610375,0.00006035788,0.00000280591,0.00003487645],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993162,0.0002937158,0.00005063262,0.0001628542,0.00007998037,0.00005810549,0.00002059367,0.000003687441,0.00001422842],"genre_scores_gemma":[0.9997897,0.00003337629,0.00009141192,0.000003845198,0.00007246725,0.000001583909,0.000005165172,0.000002063895,4.156333e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01077658,"threshold_uncertainty_score":0.1654611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190680138731366,"score_gpt":0.2263542112204907,"score_spread":0.214447409833177,"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."}}