Quantitation of Trace Metals in Liquid Samples by Dried-Droplet Laser Ablation Inductively Coupled Plasma Mass Spectrometry
Bibliographic record
Abstract
A new, discrete sample introduction approach based on laser ablation (LA) is described for the quantitation of several trace metals in aqueous samples by ICPMS. Dried microdroplets of sample, previously mixed with a sodium acetate matrix, were quantitatively ablated from a polystyrene substrate. Calibration via the method of standard additions or isotope dilution provided accurate results for Ni, Cd, and Pb in drinking water and Se in a yeast extract. Compared to conventional solution nebulization, LA sample introduction provided a 2-7-fold enhancement in absolute sensitivity and transport efficiency of 2-14% for the elements examined. Estimated detection limits are 1-7-fold poorer for the dried-droplet LA technique, primarily a result of degraded precision arising from counting statistics limitations for discrete sample introduction. On the basis of the several-second half-width of the resulting transient signals, sample throughput can be in the range of 250 samples per hour. Additionally, integration of the transient signal should eliminate contributions to elemental fractionation from the LA step. Dried-droplet LA-ICPMS offers several advantages over its counterpart, ETV-ICPMS, with respect to background intensity, throughput, and ease of desorption.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".