Otoliths as indicators of trace element exposure in freshwater fish: a mesocosm experiment with manganese and an examination of hydro-impoundment on otolith trace element signatures
Bibliographic record
Abstract
Through biomonitoring, organisms are measured to determine levels of contamination or exposure. In freshwater, biota like fish are used to represent whole communities due to their ecological/commercial relevance. In fish, soft tissues are typically used for trace element analyses although their potential for depuration, transformation, and contaminant re-compartmentalization makes them applicable for only short-term biomonitoring. Alternatively, metabolically inert calcified tissues (e.g., otoliths) have been found useful in long-term trace element biomonitoring. Biomonitor utility was demonstrated through two studies. The first being a mesocosm study on baitfish species exposed to MnSO4 in which otolith chemical signatures were compared with the ambient mesocosm environment. Under study conditions, fish otolith biomonitors were ineffective at detecting manganese. The second study utilized fish otoliths to measure the effect of impoundment by comparing water and otolith trace element concentrations between impounded and non-impounded waterbodies. Otolith signatures successfully discriminated based on impoundment status and species.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".