Fractionation and metabolic turnover of carbon and nitrogen stable isotopes in black fly larvae
Bibliographic record
Abstract
Diet-tissue fractionation factors and metabolic turnover rates of delta15N and delta13C were assessed in laboratory-reared black fly (Simulium vittatum IS-7) larvae fed isotopically distinct diets. Five treatments consisted of using food with different delta15N signatures throughout the experiments (19-26 days), a sixth shifted from a low to high delta15N signature diet (uptake) on day 14, and the last shifted from a high to low delta15N signature diet (elimination) on day 14. In the larvae, diet-tissue fractionation factors for delta13C, which were in steady state with food, ranged from -0.61 to 2.0, with a median of 1.87. The delta15N diet-tissue fractionation factors were mostly negative, ranging from +2.85 to -24.96 per thousand, with a single positive value from the elimination treatment in which larval delta15N did not achieve steady state with the food. Diet-tissue fractionation factors also had a significant negative relationship (r2 = 0.98) with delta15N values in the food suggesting that nitrogen diet-tissue fractionation factors are 15N concentration-dependent. The delta15N of shed head capsules and feces were enriched in 15N and could be mechanisms for elimination of 15N by the larvae. For delta15N, metabolic turnover values based on the Hesslein model were highly consistent (0.40 to 0.43 delta15N*day(-1)) between uptake and elimination phases and across experiments and were an order of magnitude greater than growth rates. The rapid turnover of nitrogen in black fly larvae, which was orders of magnitude greater than measured in vertebrates, makes them an excellent indicator of short-term changes in nitrogen inputs to aquatic systems.
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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) | 0.000 | 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".