Fatty‐acid biomarkers and tissue‐specific turnover: validation from a controlled feeding study in juvenile <scp>A</scp>tlantic croaker <i>Micropogonias undulatus</i>
Bibliographic record
Abstract
Fatty-acid (FA) profiles of liver and muscle tissue from juvenile Atlantic croaker Micropogonias undulatus were examined over a 15 week diet-switch experiment to establish calibration coefficients (CC) and improve understanding of consumer-diet relationships for field applications. Essential FAs [docosahexaenoic acid (DHA), 22:6n-3 and eicosapentaenoic acid (EPA) , 20:5n-3] decreased and 18:2n-6 increased in tissues of M. undulatus fed diets with increasing proportions of terrestrial v. marine lipid sources. Non-linear models used to estimate the incorporation rate and days to saturation of per cent 18:2n-6 in tissues showed that livers incorporated 18:2n-6 faster than muscle, but the proportions of 18:2n-6 in muscle were higher. CCs were established to determine proportions of FA deposition in tissues relative to diet. Many CCs were consistent amongst diet treatments, despite growth and dietary differences. The CCs can be used to discern FA modification and retention within tissues and as tools for future quantitative estimates of diet histories. Incorporation rates and CCs of 18:2n-6 were applied to a sub-set of field samples of wild M. undulatus to understand habitat use and feeding ecology. Altogether, these results suggest that FAs provide a time-integrated measure of diet in aquatic food webs and are affected by tissue type, growth rate and the influence of mixed diets.
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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 | 0.001 |
| 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) | 0.000 | 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".