A Preconcentration/Matrix Reduction Method for the Analysis of Rare Earth Elements in Seawater and Groundwaters by Isotope Dilution ICPMS
Bibliographic record
Abstract
A simple method of simultaneous preconcentration and matrix reduction was developed for the analysis of rare earth elements (REEs) in seawater and groundwater by ID ICPMS. The method utilizes partitioning of the REEs with solid hydroxides to separate them from soluble matrix species (e.g., Ba2+, NOM, seawater salts). Acidified samples were spiked and equilibrated with an enriched isotope cocktail (142Ce, 145Nd, 161Dy, 171Yb). Aqueous NH3 was then added to the spiked samples to induce the coprecipitation of the REEs with a small fraction of the natural Mg2+ as Mg(OH)2. The samples were centrifuged and the precipitate was rinsed to remove more than 99.8% of the Ba2+ along with the matrix salts. The precipitate was dissolved in 400 microL of 10% HNO3 for ICPMS analysis. The four spiked elements, determined by isotope dilution, served as internal standards for the remaining REEs. Analysis of NASS-4 and NASS-5 seawater reference materials showed good agreement with published values. Calculated limits of detection for a 1.65-g sample ranged from 0.1 pg/g for the light REEs to 0.02 pg/g for the heavy REEs. The reagent blanks ranged from a high of 0.28 pg/sample for Ce to a low of 0.0036 pg/sample for Tb.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".