Application of the high-speed self-reversal background corrector to the determination of cadmium by chemical vapor generation atomic absorption spectrometry
Bibliographic record
Abstract
Concentrations of cadmium (Cd) in extracting solutions (neutral salts) from contaminated soils are often too low to be determined by conventional flame atomic absorption spectrometry. For this reason, determination of Cd requires sensitive analytical methods free from interference problems generated by samples. In this context, vapor generation atomic absorption spectrometry (HGAAS) was combined with a high-speed self-reversal background corrector. This new approach was successfully applied after optimization of the analytical parameters to obtain a maximal absorbance signal of the volatile Cd species. The optimum condition was achieved with a 3% (m/v) NaBH4 in 1.5% (m/v) NaOH reducing solution and a solution containing 0.3 mol/L HNO3. The detection limit was 1 ng mL–1 under the previous conditions and the relative standard deviation was up to 5% for 10 replicate analyses of Cd at 0.2 and 1 ng mL–1, reflecting a very highly sensitive and reproducible method. Moreover, the results showed that the proposed combination was an efficient method to overcome the interference problems caused by different coexisting cations, As, Al, Ca, Cu, Fe, Mg, Mn, Ni, Pb, Se and Zn, up to 10 µg mL–1. The method was validated with analyses of two standard reference materials and was used for Cd determination in 0.01 mol/L CaCl2 extracts from contaminated kitchen garden soils. The data were compared with those obtained by two other more conventional methods, electrothermal atomic absorption spectrometry (ETAAS) and flame atomic absorption spectrometry (FAAS). The analytical results obtained by the ETAAS and HGAAS were in a good agreement, suggesting the suitability of the method for Cd determination in 0.01 mol/L CaCl2 extracting solution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".