Mercury and cadmium in striped dolphins (Stenella coeruleoalba) stranded along the Southern Tyrrhenian and Western Ionian coasts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pollution from heavy metals is becoming a serious and widespread problem due to their persistent and bioaccumulative nature, moreover in the Mediterranean Sea, threatening food safety and the health of humans and marine animals. Cadmium and mercury in particular, are considered two of the most toxic metals to living organisms. Their presence is associated with the contribution of human activity, implying an increased level in the different environmental compartments and the inevitable bioaccumulation in the food chain.In this study, levels of cadmium and mercury were determined in liver, kidney, and muscle tissue of dolphinid specimens of Stenella coeruleoalba stranded in different locations along the coastal areas of the Tyrrhenian and Ionian Sea in Southern Italy, during the period 2015–2018 by Atomic Absorption Spectrophotometry. Data were compared with those reported for other locations along the Mediterranean sea. The correlations between biometric data (body length, weight and gender) and cadmium and mercury concentrations in samples of cetaceans were statistically analysed in order to investigate the risk these contaminants may pose to the delphinids health.Examination of the pattern of contaminants revealed a significantly high distribution for mercury in all the matrices analyzed (liver, kidney and muscle tissue). On the contrary, elevated concentrations of cadmium were found only in liver (range: 0.005 - 8.95 mg/kg w.w.) and kidney (range: 0.005 - 34.1 mg/kg w.w.) due to accumulator role of these organs in long-term exposures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 it