The direct and accurate determination of major elements Ca, K, Mg and Na in water by HR-ICPMS
Bibliographic record
Abstract
Abstract A direct, accurate and precise method is reported for major elements Ca, K, Mg and Na measurements in river and drinking water using a high resolution ICP-MS. Double isotope dilution calibration was used for the determination of Mg whereas the combined standard addition and internal standardization (Sc) was used for Ca, K and Na measurements. The method is validated by analysis fresh water SLRS-5, SLRS-6 and SRM1640a with satisfactory results characterized by high precisions of 0.055% to 0.66% RSD (or 0.29–1.8% relative combined uncertainty) for all four analytes, superior to those reported in earlier studies. As noted, use of internal standard Sc has significantly (3–33 times) improved measurement precisions for Ca, K and Na compared to standard addition calibration alone. The proposed method was applied for the determination of major elements Ca, K, Mg and Na in a candidate drinking water CRM AQUA-1. Values of 1.908 ± 0.007 µg g −1 , 8.27 ± 0.14 µg g −1 , 0.660 ± 0.010 µg g −1 and 13.76 ± 0.05 µg g −1 ( u , k = 1) were obtained for Mg, Ca, K and Na in AQUA-1 drinking water, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".