ICP-OES assisted determination of the metal content of some fruit juices from Yemen's market
Bibliographic record
Abstract
The levels of Cd, Cr, Cu, Pb, Zn, Sn, and Fe of 37 samples of 6 types of fruit juices (orange, mango, guava, pineapple, peach, and mixed fruit) marketed by different brands and of easy access in Sana'a food stores, Yemen (2019) were evaluated using the inductively coupled plasma-optical emission spectrometry (ICP-OES) technique. Traces of chromium were detected in two fruit juices and cadmium in seven juices. One sample presented a highly elevated Pb-content. High level of tin, iron and zinc were detected in some fruit juices. Metal content in some fruit juices sold on the Yemeni market exceeded the permissible limits set by health organizations for drinking water. The origin of metal contamination could be likely linked to war condition even though it is difficult to be totally affirmative, so far. Fruit juices available on the Yemeni market are globally safe, nonetheless, further risk-based surveillance studies must be carried out to decrease child exposure to toxic metals from fruit juice sources.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".