Isotopic tissue turnover and discrimination factors following a laboratory diet switch in Colorado pikeminnow (<i>Ptychocheilus lucius</i>)
Bibliographic record
Abstract
Stable isotope ecology has made great strides in quantifying energy transfer through food webs. However, trophic inferences gleaned from field-collected data can be limited when isotopic turnover and isotopic discrimination factors (Δ13C or Δ15N) are unknown. We quantified isotopic turnover and discrimination factors using an isotopic diet switch in the endangered Colorado pikeminnow (Ptychocheilus lucius). The estimated half-life for δ13C was 62 days or a 33% increase in mass and δ15N averaged 133 days or a 52% increase in mass. Growth and metabolic processes both contributed to rates of turnover, but metabolic processes had a stronger effect in δ13C than in δ15N. Lipid-corrected δ13C values resulted in discrimination factors of Δ13C between 0.67 and 0.82 and Δ15N between 2.31 and 2.93, values similar to other fishes. These results suggest sampling fin tissue may be a useful, nonlethal tool for isotopic studies. Fins also demonstrated enrichment in 13C that was not linked to the diet switch, highlighting the importance of controls in isotopic diet switch studies to verify species- and diet-specific estimates of isotopic turnover rates.
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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".