Maternal and embryonic trace element concentrations and stable isotope fractionation in the smalleye smooth-hound (Mustelus higmani)
Bibliographic record
Abstract
Here, we evaluate maternal offloading of 16 trace elements (Essential: Co, Cr, Cu, Fe, Mn, Ni, Se and Zn; Nonessential: Al, As, Ba, Cd, Hg, Pb, Tl and U) and determine mother-offspring isotopic fractionation of δ13C and δ15N in muscle and liver tissue of four pregnant Mustelus higmani and 18 associated embryos sampled from the Amazon Coast of Brazil. Embryo muscle tissue had significantly higher concentrations of most trace elements when compared to mothers, with the exception of Hg. Embryo liver accumulated more nonessential elements than muscle (n = 7 vs. 0, respectively), while the Se:Hg molar ratio was >1 in liver and muscle of both mothers and embryos. Livers of embryos were moderately enriched in δ13C and δ15N when compared to that of their mother. Negative correlations were observed between embryo body length and δ13C and trace elements concentrations. We conclude that mothers offload a large portion of all essential elements and Al, As and Pb to their young and that the isotopic fractionation of embryos reflects maternal diet and habitat occupied, with δ13C diluted with embryonic growth. We also show that muscle and liver accumulate trace elements at different rates relative to the body length of embryos. The Se:Hg molar ratio suggests that Se could play a protective role against Hg toxicity during early stages of M. higmani embryonic development.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".