Can Diet-Dependent Factors Help Explain Fish-to-Fish Variation in Thiamine-Dependent Early Mortality Syndrome?
Bibliographic record
Abstract
Abstract To provide insight into the reasons why offspring of certain salmonine females exhibit early mortality syndrome (EMS) in the Great Lakes whereas others do not, we measured the egg concentrations of potential biochemical markers (stable isotopes of nitrogen and carbon, fatty acid signatures, and lipid-soluble carotenoids and vitamins) that are indicative of differing food web and trophic structure. To corroborate the presence of EMS, we also measured the egg content of thiamine vitamers. For all the stocks of coho salmon Oncorhynchus kisutch and Chinook salmon O. tshawytscha we studied, there was a very high correspondence between EMS and low concentrations of unphosphorylated thiamine in unfertilized eggs. For salmonine stocks in the Platte River, Thompson Creek, and the Swan River, Michigan, small but significant shifts occurred in measures of egg carotenoids, retinoids, δ15N depletion, and fatty acid profiles of fish producing normal offspring relative to those exhibiting EMS. Egg thiamine concentrations in Chinook salmon from the Little Manistee River, Michigan, in the low-EMS group were only marginally above the threshold for EMS induction. Along with this small thiamine differential, there was no evidence of differing food web or dietary factors between EMS-positive and normal Chinook salmon from the Little Manistee River. Further investigations are required to determine the potential dietary sources for the observed differences in biochemical markers between EMS-positive and normal fish. These findings are generally consistent with the hypothesis that a more diverse forage base may help to limit overall dietary content of species that contain thiaminase, such as alewives Alosa pseudoharengus, and may lead to improved embryonic survival for feral salmonids.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".