Assessment of Modified Matrix Solid-Phase Dispersion as Sample Preparation for the Determination of CH<sub>3</sub>Hg<sup>+</sup> and Hg<sup>2+</sup> in Fish
Bibliographic record
Abstract
This paper reports, for the first time, the development of an analytical method employing modified matrix solid-phase dispersion (MSPD) for the extraction of CH3Hg(+) and Hg(2+) species from fish samples. Separation and determination of mercury species were performed by gas chromatography coupled to mass spectrometry (GC/MS). Important MSPD parameters, such as sample mass, type and mass of solid support, concentration of extraction solution (HCl and NaCl), and stirring time, were investigated by the response surface methodology. The derivatization step and the separation of mercury species were also evaluated for the determination by GC/MS. Quantitative recoveries were obtained with 0.2 g of fish sample, 0.5 g of SiO2 as the solid support, 0.5 mol L(-1) NaCl and 4.2 mol L(-1) HCl as the extraction solution, and 1 min stirring time. The MSPD method showed to be suitable for the extraction and determination of mercury species in certified reference materials of dogfish liver (DOLT-3) and dogfish muscle (DORM-2). It had good agreement (about 99%) with the certified values, and the relative standard deviation was lower than 9.5%. The limits of detection were 0.06 and 0.12 μg g(-1), for CH3Hg(+) and Hg(2+), respectively. A matrix effect was observed, and the quantification was carried out by the matrix-matched calibration. The method was applied to tuna fish ( Thunnus thynnus ), angel shark ( Squatina squatina ), and guitarfish ( Rhinobatos percellens ) samples. The results of the mercury speciation by MPSD and GC/MS were compared to the total mercury concentration determined by flow injection cold vapor generation inductively coupled plasma mass spectrometry, after microwave-assisted digestion. Agreement ranged from 102% to 105%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".