Speciation of cationic arsenic species in seafood by coupling liquid chromatography with hydride generation atomic fluorescence detection
Bibliographic record
Abstract
A method was developed for determining arsenobetaine (AB), arsenocholine (AC), trimethylarsine oxide (TMAO) and tetramethylarsonium ion (TMA+) in seafood products. The arsenic species were extracted from the matrix by methanol–water and the extracts were quantified by high-performance liquid chromatography coupled with thermo-oxidation hydride generation atomic fluorescence spectrometry (HPLC–thermo-oxidation–HG-AFS). The variables affecting each stage of the methodology were optimized. The analytical features of the method (recovery, precision, limit of detection and linearity range) were calculated for each arsenical species. The lowest limit of detection was obtained for TMAO (0.0009 µg g−1, dry mass), whereas AC was the arsenic species with the highest LOD (0.0063 µg g−1, dry mass). The precision of the method varied between 0.7% for AB and 8.4% for TMA+. The recovery percentage was greater than 97% for all species. The proposed procedure was applied to reference materials: DORM-2 (Dogfish muscle, National Research Council of Canada), NFA-Shrimp and NFA-Plaice (National Food Agency of Denmark). The results were compared with the values obtained by other authors.
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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 | 0.001 |
| 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) | 0.002 | 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".