Development of a Bacterial Enzyme‐Based Biosensor for the Detection and Quantification of Selenate
Bibliographic record
Abstract
Abstract An enzymatic biosensor has been developed for the determination of selenate (SeO42−), in which selenate reductase (SeR) is chemically attached to a gold disk electrode by lipoic acid N‐hydroxysuccinimide ester as linker, allowing the catalytic reduction of the SeO42− to SeO32−. Modification of the gold electrode was characterized by X‐ray photoelectron spectroscopy (XPS), time‐of‐flight secondary ion mass spectroscopy (ToF‐SIMS), and electrochemistry. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) measurements were performed in different buffers for selenate determination. Under optimum conditions, the calibration curve was linear over the range 7.0–3900.0 μg L−1 with limits of detection and quantification of 4.97 and 15.56 μg L−1, respectively. The possible interference of the relevant oxyanions SO42−, NO3−, NO2−, PO43− and AsO43− in the determination of SeO42− was studied. Finally, the proposed biosensor was used to determine SeO42− with recovery between 95.2 and 102.4 % in different real water 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".