A Facile Electrochemical Sensor Labeled by Ferrocenoyl Cysteine Conjugate for the Detection of Nitrite in Pickle Juice
Bibliographic record
Abstract
Simple and facile electrochemical sensors for nitrite detection were fabricated by directly depositing ferrocenoyl cysteine conjugates Fc[CO-Cys(Trt)-OMe]2 [Fc(Cys)2] or Fc[CO-Glu-Cys-Gly-OH] [Fc-ECG] on screen-printed electrodes (SPEs). The modified carbon electrodes were characterized by scanning electron microscopy (SEM), cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Results indicated that Fc-ECG/SPE sensor showed enhanced current response and a lower overpotential than Fc(Cys)2/SPE sensor for nitrite detection. Optimal operating conditions were estimated for nitrite detection by DPV. The concentration of nitrite showed a good linear relationship with the current response in the range of 1.0–50 μmol·L−1 and with 0.3 μmol·L−1 as the concentration for limit of detection. There were no interferences from most common ions. The development of this electrochemical sensor was used for nitrite detection in pickled juice with a R.S.D. lower than 2.1% and average recovery lower than 101.5%, which indicated that disposable electrochemical sensor system can be applied for rapid and precise nitrite detection in foods.
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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 | 0.001 |
| 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".