Incorporation of carbon and nitrogen isotopes in age-0 walleye (<i>Sander vitreus</i>) tissues following a laboratory diet switch experiment
Bibliographic record
Abstract
Trophic dynamics are often described by following the exchange of naturally occurring isotopes through aquatic communities. However, without experimentally derived isotopic turnover rates and discrimination factors for each species, tissue, and life stage, these trophic models can be misleading. We conducted a laboratory diet shift experiment to describe isotopic turnover and discrimination in age-0 walleye (Sander vitreus) dorsal muscle and gutted carcass samples. Although turnover of dietary δ13C (half-life: 10–12 days) and δ15N (half-life: ∼13 days) signatures was relatively rapid, the diet change was undetected in both tissues during a short transitional period (up to 1.2 times shorter in muscle). Our discrimination estimates generally conform to those of other fishes (ΔCarbon = 0.91, ΔNitrogen = 1.6), but were 30%–50% higher in muscle tissues than in gutted carcass samples. The assumption that young walleye tissues are in equilibrium with their diet is untrue for weeks following a diet shift, and when incorporated, discrimination factors differ between tissues. We provide tissue-specific parameters that remove uncertainty associated with the analysis of field collected isotopic age-0 walleye data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".