Effects of temperature and elemental concentration on the chemical composition of juvenile yellow perch (Perca flavescens) otoliths
Bibliographic record
Abstract
Otolith microchemistry studies assume that a relationship exists between the concentration of trace elements in the environment and otolith chemical composition. Although this assumption has been tested using marine and estuarine fish in controlled laboratory experiments, the relationships among temperature, ambient elemental concentration, and otolith chemical composition for freshwater species is not well documented. Here, juvenile yellow perch ( Perca flavescens ) were reared under different concentrations of four elements (Ba, Mg, Mn, and Sr) crossed with three temperatures (10 °C, 15 °C, and 20 °C) to determine the interactive influence of ambient elemental concentrations and temperature on otolith chemical composition. Sr:Ca and Ba:Ca were significantly related to ambient elemental concentrations, but Mg:Ca and Mn:Ca were not. Although the relative influence of temperature was less than that of ambient elemental concentrations, Sr:Ca, Ba:Ca, and Mn:Ca were all influenced by either water temperature or the interaction between temperature and elemental concentration, but the direction of the temperature effect differed for each element. Patterns in our partition coefficients are consistent with the idea that uptake of strontium facilitates uptake of barium. Overall, yellow perch otolith element composition was influenced primarily by ambient Sr and Ba concentrations, but temperature could potentially confound the results of otolith microchemistry studies.
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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".