Estimation of Seasonal Risk Caused by the Intake of Lead, Mercury and Cadmium through Freshwater Fish Consumption from Urban Water Reservoirs in Arid Areas of Northern Mexico
Bibliographic record
Abstract
Bioavailability and hence bioaccumulation of heavy metals in fish species depends on seasonal conditions causing different risks levels to human health during the lifetime. Mercury, cadmium and lead contents in fish from Chihuahua (Mexico) water reservoirs have been investigated to assess contamination levels and safety for consumers. Muscle samples of fish were collected across the seasons. Lead and cadmium were analyzed by inductively coupled plasma-optical emission spectrometry, and mercury by cold-vapor atomic absorption spectrometry. The highest concentrations of cadmium (0.235 mg/kg), mercury (0.744 mg/kg) and lead (4.298 mg/kg) exceeded the maximum levels set by European regulations and Codex Alimentarius. Lead concentrations found in fish from three water reservoirs also surpassed the limit of 1 mg/kg established by Mexican regulations. The provisional tolerable weekly intake (PTWI) suggested by the World Health Organization for methyl mercury (1.6 µg/kg bw per week) was exceeded in the spring season (1.94 µg/kg bw per week). This might put consumers at risk of mercury poisoning.
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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".