Determination of Total Chromium in Seawater by Isotope Dilution Sector Field ICPMS Using GC Sample Introduction
Bibliographic record
Abstract
A method for the accurate determination of total Cr in seawater by isotope dilution (ID) sector field inductively coupled plasma mass spectrometry (SF-ICPMS) using GC as a means of sample introduction is described. Chromium was reduced to Cr(III) by addition of SO(2)-saturated water and derivatized with trifluoroacetylacetonate (TFA) to form volatile Cr(TFA)(3). Derivatized analyte was either extracted into hexane or directly sampled by solid-phase microextraction (SPME) using a poly(dimethylsiloxane)-coated fused-silica fiber for GC/SF-ICPMS analysis. With medium resolution required to efficiently separate argide, argon chloride and oxide interferences, a concentration of 0.154 +/- 0.013 ng mL(-1) (1 SD, n = 4) was obtained for Cr in NRCC seawater CRM CASS-4 using a 1-microL hexane extract, in agreement with the certified value of 0.144 +/- 0.029 ng mL(-1) (95% confidence interval). A detection limit of 20 pg mL(-1) was achieved. Low-resolution GC/SF-ICPMS in combination with solvent-free SPME sampling effectively eliminated spectroscopic interferences, yielding a concentration of 0.132 +/- 0.004 ng mL(-1) (1 SD, n = 4) for Cr in CASS-4 with a method detection limit of 3.9 pg mL(-1). By comparison, SPME sampling with GC/SF-ICPMS in medium-resolution mode provided a concentration of 0.146 +/- 0.013 ng mL(-1) (1 SD, n = 4) and a method detection limit of 9.1 pg mL(-1).
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".