Performance review of a fast HPLC-UV method for the quantification of chlorogenic acids in green coffee bean extracts
Bibliographic record
Abstract
The aim of this study was to test the performance of a HPLC method, designated for rapid quantification of chlorogenic acids (CGA) in green coffee extract (GCE). The precision statistics associated with the method were assessed using three independent laboratories with five samples analyzed in triplicate. Seven main CGA isomers (3-CQA, 5-CQA, 4-CQA, 5-FQA, 3,4-diCQA, 3,5-diCQA and 4,5-diCQA) were quantified. The concentration of total CGA in the samples varied from 32.24% to 52.65% w/w. The repeatability and reproducibility standard deviations for the determination of individual isomers varied, respectively, from 0.01 to 0.28 and 0.05-1.59. The repeatability and reproducibility standard deviations of the calculated total CGA, corresponding to the sum of the seven main CGA isomers, varied respectively, from 0.17 to 0.58 and 0.55-2.01. The fast HPLC method evaluated in this study was considered precise and appropriate for the determination of CGA in GCE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".