A comparison of techniques for preparing fish fillet for ICP-AES multielemental analysis and the microwave digestion of whole fish
Bibliographic record
Abstract
Four catfish fillet homogenate treatments before multielemental metal analysis by simultaneous inductively coupled plasma/atomic emission spectroscopy were compared in triplicate. These treatments were: nitric acid wet-ashing by Parr bomb digestion; nitric acid wet-ashing by microwave digestion; tetramethylammonium hydroxide/nitric acid wet digestion; and dry-ashing. The tetramethylammonium hydroxide/nitric acid method was imprecise (coefficients of variation > 20%). The dry-ashing method was fast and sensitive but had low recoveries of 50% for spiked Pb and Al and was not as precise as the Parr bomb or microwave treatments. The Parr bomb method was the most precise method but was less sensitive than the microwave method which had nearly the same precision. The microwave method was then adapted to homogenates of small whole fish < or = 3 cm in length. The whole fish homogenate required more vigorous digestion conditions, and addition of more acid after the evaporative step because of the presence of less oxidizable and acid-soluble components than fillet. The whole fish homogenate was also more heterogeneous than catfish fillet. A quality assurance protocol to demonstrate homogenate uniformity is essential. The use of a non-specialized microwave oven system allowed precise results for fillet and whole fish homogenates.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".