Facile caffeine electrochemical detection via electrodeposited Ag nanoparticles with modifier polymers on carbon paste sensor at aqueous and micellar media
Bibliographic record
Abstract
The analysis and detection of caffeine (Caf) is very useful due to its widespread usage in several daily consumed beverages, food products, and pharmacological preparations with various physiological effects. The preparation of a newly electrodeposited Ag nanoparticles – cellulose acetate phthalate (CAP) – chitosan (Chit) modified carbon paste (ACCMCP) sensor for sensitive determination of Caf in 0.01 mol L−1 H3PO4 solution (pH 1.0–5.0) both in aqueous and micellar media (0.5 mmol L−1 SDS) was achieved. The interaction of Caf was monitored using electrochemical techniques such as cyclic voltammetry, differential pulse voltammetry, electrochemical impedance spectroscopy, and chronoamperometry, and surface characterization was carried out using X-ray diffraction, scanning electron microscope, and energy dispersive X-ray techniques. The linear detection range of Caf was between 4 and 500 μmol L−1 (r2 = 0.955) and the limit of detection obtained from the calibration plot was 0.252 μmol L−1. The sensor was applicable for detecting Caf in numerous real samples with recoveries from 98.03% to 101.60% without interference of any accompanying species, which ensures high method selectivity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".