A new and sensitive method for the determination of trace arsenic using differential pulse polarography
Bibliographic record
Abstract
A new and simple differential pulse polarographic method has been developed for the trace determination of arsenic. When selenite was added into solutions of some ions such as copper, lead, cadmium, zinc, and chromium, their differential pulse polarographic peak decreased. A new reduction peak appeared at a more positive potential than the ion present and it was always higher than the corresponding reduction peak of the ion. Thus, we made use of this interference for the trace determination of As(III). By the addition of selenite onto As(III), a new As−Se intermetallic compound peak was formed at about −0.35 V (pH at about 1.0–2.0). The trace arsenic concentration could be determined simply from this peak by the addition of standard arsenic into a polarographic cell. In the presence of large amounts of selenite, 2 × 10−7 mol/L As(III) could be determined from this peak precisely. With the newly established method, the limit of detection was 1 × 10−8 mol/L (S/N = 3). Among the most common cations and anions, only Cd−Se and Pb−Se intermetallic compound peaks had an overlap with the As−Se peak. This interference could be eliminated simply by the addition of EDTA. This method was applied successfully for the determination of arsenic in a digested beer sample.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".