A disposable sticky electrode for the detection of commercial silver NPs in seawater
Bibliographic record
Abstract
The ability to perform efficient and affordable field detection and quantification of nanoparticles in aquatic environmental systems remains a significant technical challenge. Recently we reported a proof of concept of using 'sticky' electrodes for the detection of silver nanoparticles (Tschulik et al 2013 Nanotechnology 29 295502). Now a disposable electrode for detection and quantification of commercial Ag nanoparticles in natural seawater is presented. A disposable screen printed electrode is modified with cysteine and characterized by sticking and stripping experiments, with silver nanoparticle immobilization on the electrode surface and subsequent oxidative stripping, yielding a quantitative determination of the amount of Ag nanoparticles adhering to the electrode surface. The modified electrode was applied to natural seawater to mimic field-based environmental monitoring of Ag NPs present in seawater. The results demonstrated that commercial Ag NPs in natural seawater can be immobilized, enriched and quantified within short time period using the disposable electrodes without any need for elaborate experiments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".