Hepatic and nephric mercury and selenium concentrations in common mergansers, <i>mergus merganser</i>, from baltic region, Europe
Bibliographic record
Abstract
The subject of the present study was the piscivorous common mergansers (Mergus merganser). The total mercury (THg), methylmercury (MeHg), selenium (Se) inorganic mercury (InHg; THg - MeHg), percentage of THg that is MeHg (%MeHg), molar ratios (THg:Se, MeHg:Se, InHg:Se), and their mutual relations in livers and kidneys were determined in ducks from an Se-deficient area in Poland. The authors verified a hypothesis that, as a result of living in an Se-deficient region, mergansers from Poland should have higher THg:Se ratios than other waterbirds with similar THg tissue levels. Although a comparison of healthy mergansers from Poland and Canada showed similar THg tissue contents, the group in the present study had a few times lower Se levels and higher THg:Se ratios (overall means >1.7 in both livers and kidneys in all studied individuals) than the Canadian group and other European and North American waterbirds. The authors found significant correlations between various relations, including MeHg-THg, InHg-THg, Se-THg, %MeHg-THg, InHg/%THg-THg, %MeHg/THg-InHg, %InHg/THg-InHg, MeHg:Se-THg:Se, InHg:Se-THg:Se, InHg:Se-MeHg:Se in liver and InHg-THg, Se-THg, Se-InHg, %MeHg-THg, %MeHg-InHg, %InHg/THg-InHg, THg:Se-THg, InHg:Se-THg, MeHg:Se-MeHg, THg:Se-InHg, InHg:Se-InHg, and InHg:Se-THg:Se in kidney. It is likely that the main factor responsible for the high value of THG:Se ratio (>1) in mergansers from Poland is Se deficiency in central and northern Europe. Therefore, this element is unlikely to participate in the detoxification of Hg in these birds.
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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 | 0.000 |
| 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) | 0.000 | 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".