Maternal Transfer and Effects of Selenium on Early Life Stage Development of Redside Shiner (<i>Richardsonius balteatus</i>)
Bibliographic record
Abstract
Abstract Maternal transfer of selenium (Se) to developing fish eggs during vitellogenesis can cause larval deformity and mortality. Previous studies have shown wide variation among fish species in both the magnitude of maternal transfer (exposure) and the egg Se concentration causing effects (sensitivity). We studied maternal transfer and effects of Se on early life stage development, survival, and growth of redside shiner (Richardsonius balteatus), a small-bodied cyprinid that has been reported to have relatively high ovary:muscle Se concentration ratios. Gametes were collected from lentic areas in southeast British Columbia (Canada) with a range of dietary Se concentrations related to weathering of waste rock from coal mining. Eggs were fertilized and reared in the laboratory from hatch to the onset of exogenous feeding. Larvae were assessed for survival, length, weight, Se-characteristic deformities, and edema. Eggs from a total of 56 females were collected, with egg Se concentrations from 0.7 to 28 mg/kg dry weight. Maternal transfer varied among sites, with egg:muscle Se concentration ratios ranging from <1 to >4. We also found that sampling residual ovaries can overestimate Se concentrations in ripe eggs by up to a factor of 5.7. A correlation between larval weight and egg Se concentration was identified, although the relationship was weak (r2 < 0.1) and appeared to be a site effect. No other relationships were observed between larval endpoints and egg Se concentrations up to the highest concentration tested, indicating that the effects threshold for this species may be >28 mg/kg dry weight in eggs. These data indicate that redside shiner is less sensitive to maternally transferred Se than most other tested fish species. Environ Toxicol Chem 2023;42:2350–2357. © 2023 SETAC
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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".