Direct Arsenic Determination in Exposed Embryos of Zebrafish (<i>Danio rerio</i>) with Zeeman Electrothermal Atomic Absorption Spectrophotometry
Bibliographic record
Abstract
Several methods of analysis have been evaluated for the determination of the arsenic content in zebrafish embryos (Danio rerio). The methods have been developed based on waste minimization, while sample treatment was exploited to attend the standards of clean chemistry. The ultimate goal of developing a method to directly introduce whole single embryos into the electrothermal furnace atomic absorption spectrometer (ETAAS) was accomplished after optimization of instrument parameters and matrix modifiers. The significant matrix effects due to the complexity of the sample were overcome by the use of a palladium modifier and hydrogen peroxide as an oxidizing agent to aid in the mineralization of the sample during the pyrolysis. The results obtained from this direct method for arsenic analysis were in agreement with those from more common sample preparation methods of acid digestion or ultrasonic extraction. The speed of the ultrasonic method and use of environmentally safe reagents makes this a more favorable technique than acid digestion. The single embryo direct introduction method, however, is preferred due to its ability to measure whole single samples without any sample pretreatment, and furthermore allows for evaluation of the variability of arsenic accumulation between individual samples. The ETAAS method developed has been validated by inductively coupled plasma mass spectrometry (ICP-MS).
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".