Determining the Lithium and Calcium Concentrations in Canned Tuna Fish in Iran
Bibliographic record
Abstract
Backgrounds and aims: Nutrition is the main way to receive the trace elements that human body needs. Lithium (Li) and calcium (Ca) are two trace elements, which have important roles in human body. There are a few studies about the amounts of calcium and lithium in canned tuna fish. The aim of this study was to determine the concentrations of calcium and lithium in canned tuna fishes. Materials and Methods: To this aim, 150 samples of canned tuna fishes from two well-known brands (Majid and Poolak), marketed in Khuzestan province of Iran, were obtained. Li contents of the samples were measured by atomic absorption spectrometry (AAS) with atomization in graphite furnace. Ca contents of the samples were measured by AAS using nitrous oxide-acetylene flame. Results: The mean concentrations of calcium in canned tuna fish of Majid and Poolak brands were 448.47 and 398.22 mg/kg, respectively. Additionally, the mean concentrations of lithium in canned tuna fish of Majid and Poolak brands were 38.42 and 39.67 mg/kg, respectively. The mean concentration of calcium in the investigated canned tuna samples fish was lower than provisional tolerable intake (PTI) per day (1000 ppm) set by World Health Organization (WHO) and Environmental Protection Agency (EPA). However, the mean concentration of lithium in the studied canned tuna fish samples was higher than PTI/day (0.650- 3.1 ppm) Set by EPA. Conclusion: The results of current study showed that the marine food industries need a more-precise and serious monitoring by public health organizations. Additionally, protecting the marine environment from pollutions is an obligation that needs the attention of related organizations and authorities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".