{"id":"W2526819518","doi":"10.1515/pac-2015-0705","title":"Extraction for analytical scale sample preparation (IUPAC Technical Report)","year":2016,"lang":"en","type":"article","venue":"Pure and Applied Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Chemistry; Sample preparation; Extraction (chemistry); Chemical nomenclature; Sample (material); Scale (ratio); Biochemical engineering; Process engineering; Complex matrix; Solvent extraction; Chromatography; 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":[0.006865371,0.004021101,0.00208273,0.008995259,0.002370027,0.002283132,0.003592476,0.002264641,0.05417913],"category_scores_gemma":[0.007721785,0.001873557,0.001765047,0.005986669,0.001717175,0.002955329,0.00285909,0.004378061,0.08448936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009901013,"about_ca_system_score_gemma":0.00327296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017692,"about_ca_topic_score_gemma":0.001729336,"domain_scores_codex":[0.9899729,0.001603465,0.0009845783,0.001472879,0.005349586,0.0006165553],"domain_scores_gemma":[0.9944524,0.001057208,0.0005052552,0.001663382,0.002130796,0.0001909518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004963363,0.0004289227,0.001150704,0.004744421,0.0001968157,0.001296726,0.0003147173,0.001079035,0.4253043,0.01681801,0.1837804,0.3643896],"study_design_scores_gemma":[0.00006328139,0.0004145149,0.001975906,0.0006586911,0.0001103162,0.001766743,0.00005956586,0.0007591748,0.240976,0.00341303,0.7496858,0.0001169529],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006183254,0.03135293,0.8406716,0.001639856,0.006023958,0.008275,0.01871242,0.01097511,0.07616581],"genre_scores_gemma":[0.02897353,0.05106894,0.7215877,0.00245476,0.003171089,0.0154285,0.07012738,0.00375716,0.103431],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05417913,"threshold_uncertainty_score":0.1812472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02066587562649667,"score_gpt":0.3290768869321394,"score_spread":0.3084110113056427,"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."}}