Chemical analysis of endolymph and the growing otolith: Fractionation of metals in freshwater fish species
Bibliographic record
Abstract
The fractionation of metals from water to otolith is an area of research that has received relatively limited attention, especially in freshwater systems. The objectives of the present research were to study the metal partitioning between otolith and endolymph of two freshwater species: Lake trout (Salvelinus namaycush), and burbot (Lota lota). We also included the chemical analyses of water and blood from fish of the same species collected in the same area but during different years. These results provide insight regarding the partition of metals between water and fish. This is one of the first studies to provide a range of trace metal concentrations for endolymph and the growing otolith (both aragonite and vaterite) and to directly measure otolith-endolymph partition coefficients for freshwater fish. The trace elements (Mg, Sr, and Ba) most often used as otolith elemental tracers were the ones with the lowest uptake from water to blood. We found that endolymph and whole blood had similar metal concentrations, with Mg and Fe being the only elements enriched in whole blood. Results showed few significant differences in trace metal content between wild lake trout and burbot endolymph (except for K, Mg, and Ba), but significant differences existed between their aragonitic otoliths. These results suggest two different crystallization processes in these species or the presence of different proteins (and/or organic matrices) that would selectively influence elemental incorporation in the otoliths.
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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 | 0.001 | 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".