Mercury speciation in Cuban commercial edible fish by HPLC-ICP-MS using the double spike isotope dilution analysis strategy
Bibliographic record
Abstract
A sensitive and accurate quantitative method for the speciation of inorganic Hg2+ and methyl-mercury by ID-HPLC–ICP-MS has been optimised and implemented for marine fish samples. Quantitative extraction of Hg species was achieved using a 0.1% (v/v) 2-mercaptoethanol, 0.05% (w/v) L-cysteine and 0.10% (v/v) HCl solution by sonication for 30 min. Chromatographic separation of mercury species was carried out on a C8 reverse phase column with 0.05% (v/v) 2-mercaptoethanol, 0.075% (w/v) L-cysteine and 0.06 mol L−1 ammonium acetate as the mobile phase. A species specific isotope dilution analysis approach, using 201CH3Hg+ and 200Hg2+ was employed for the quantification of both species. Two biological Certified Reference Materials (DOLT-2, DORM-2) were analysed to assess the analytical performance. No significant differences were found between the obtained concentrations and the certified reference values for total Hg and CH3Hg+. The results indicate that no species interconversion reactions occurred during the used extraction and chromatographic separation procedures. The detection limits for CH3Hg+ and Hg2+ species were 7.7 and 5.2 ng g−1, respectively. The method recovery (expressed as the sum of both species contents in relation to total Hg concentration analysed by ICP-MS) was about 97 ± 5%. The procedure was applied to speciation of mercury in 12 species of the most commonly consumed commercial fish in Cuba.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".