Automated in-tube solid phase microextraction coupled with HPLC-ES-MS for the determination of catechins and caffeine in tea
Bibliographic record
Abstract
A polypyrrole (PPY) coated capillary and several commercially available capillaries (capillary GC columns) were used to evaluate their extraction efficiencies for catechins and caffeine. Compared with commercial capillaries that were currently used for in-tube solid phase microextraction (SPME), the PPY coated capillary showed better extraction efficiency for all of the compounds studied. Electrospray mass spectrometric (ES-MS) detection conditions were also investigated. After optimization of the extraction and detection conditions, a method for the sensitive and selective determination of catechins and caffeine was developed by coupling the PPY coated capillary in-tube SPME with HPLC-ES-MS. Catechins could be determined in both positive and negative ion detection modes. The detection limit (S/N = 3) for each of the studied catechins was < 0.5 ng mL-1. Caffeine could only be determined under positive ES-MS detection conditions and its detection limit was 0.01 ng mL-1. Caffeine and the five catechins in several tea samples were determined using the developed method. Small amounts of catechins were also detected in grape juice and wine samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".