Lipids in Anadromous Northern Dolly Varden (Salvelinus malma malma)
Bibliographic record
Abstract
Anadromous Arctic fish species have adapted to a particular environment by evolving unique lipid cycling strategies such as storing large amounts of lipid during times of high productivity in order to survive long migrations, spawning events, and seasonal variation in food availability. Research on lipid content and storage location in the body is very limited, especially regarding the northern Dolly Varden, a fish species important culturally and for sustenance to the Indigenous Peoples in the western Canadian Arctic that is listed as ‘Special Concern’ under Species at Risk legislation. Lipid content in anadromous Dolly Varden obtained from two marine (coastal) (summer) and two freshwater (fall) locations were examined and compared to test for differences in percent lipid between locations/seasons. Percent lipid was compared between the muscle and homogenized whole-body of individuals caught in freshwater. Muscle lipid content was significantly different between freshwater locations and one of the marine locations (~34% higher from the marine location). One marine location contained fish with unexpectedly high muscle lipid percent. A weak/moderate linear relationship was found between lipid percent in the muscle tissue and whole-body tissue of the same individuals (r2= 0.2013 when sex was an added variable; r2= 0.4204 when reproductive status was an added variable), and reproductive status influenced this relationship. Sex of the individual did not affect lipid content in the muscle nor on the relationship between percent lipids in muscle and whole-body. Changing environmental factors due to climate change such as the timing of the ice melt and phytoplankton blooms can affect energy exchange through the food web, and thus research on the nature of fluctuating energy and lipid levels is needed to aid in conservation efforts of Arctic species.
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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) | 0.001 | 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".