Validation of an analytical method for the determination of cadmium (Cd) in fish by atomic absorption spectrometry with electrothermal atomisation
Bibliographic record
Abstract
The validation of an analytical method was carried out for the determination of cadmium (Cd) in fish. The method was based on sample digestion in a microwave oven and subsequent reading using an atomic absorption spectrometer with a graphite furnace. The factorial design of experiments was applied to assess method ruggedness using the methodology of Box et al. [Box GEP, Hunter WG, Hunter JS. 1978. Statistics for experiments: an introduction to design, data analysis and model building. New York (NY): Wiley], studying the influence of sample mass, volume and concentration of acid used for sample digestion and the volume of modifier used. To study the possible matrix effect in the determination of Cd, the standard addition method was also performed. The results were treated using the OLS method. For the normality test a homoskedastic distribution was observed for the developed method and the results were adjusted to the statistical model proposed. F-tests and Student's t-tests indicated that there was no matrix effect on the calibration curve between the concentration range 1.0-10.0 µg Cd l(-1). Parameters such as selectivity, precision, decision limit, detection capability and limit of quantification were established by the method of standard addition to blank samples. The limit of quantification was 6.8 µg kg(-1). Accuracy, which was evaluated by using a certified reference material, was 107.0%. The recovery of the spiked analyte was 93.69% for the concentration of 50 µg kg(-1). Precision was defined by the coefficient of variation observed (Horrat value), estimated in terms of repeatability and reproducibility, and the values were below the limit, which is 2.0. The validation procedure confirmed the suitability of the method.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".