DETERMINATION OF TOTAL AND DISSOLVED PHOSPHORUS IN AGRICULTURAL RUNOFF SAMPLES BY INDUCTIVELY COUPLED PLASMA MASS SPECTROMETRY
Bibliographic record
Abstract
Leaching of nutrients to the drainage network is an important factor in polluting surface waters, with Phosphorus (P) often being the element of concern. Because P is strongly bound to sediments, different P fractions, including total, particulate and total dissolved P are now routinely measured. For the traditional determination of total P, a digestion followed by UV–Vis detection procedure was applied. The “true” total P content resulted from the digestion of a raw water sample containing suspended matter. Whereas the digestion performed to the sample after filtration through 0.45 μm membrane filter, gave the total dissolved P. The goal of this study was to measure the different fractions of P by ICP-MS. In the case of total P, no addition of coloring agents was necessary after the digestion process. Dissolved P was measured directly after filtration, without the previous digestion and no manipulation of the sample. Similar results were obtained by UV–Vis and by ICP-MS when measurements of demi water spiked with two different amounts of PO4 −3 were performed. Various agricultural runoff samples were digested with (NH4)2S2O8+H2SO4 30% (v/v) for total P determination. Again, similar results were obtained for both techniques. Three certified water samples from the Canadian National Water Research Institute were analyzed for dissolved P by ICP-MS. Beryllium and Sc were added as internal standards for possible drift corrections. Detection limits of 5 μg L−1 and linearity ranges from 10 μg L−1 to 5 mg L−1 were achieved.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".