The effects of dietary selenomethionine on the escape behaviours of Fathead Minnows
Bibliographic record
Abstract
Selenium is both an essential nutrient and a toxicant for animals, with only a relatively small concentration change separating the two. Toxicological work has reported various effects of selenium on fishes, including developmental impacts and deformities of the musculature and sensory systems. Behavioural ecotoxicology, a more sensitive study of toxicity, has also provided evidence that sublethal concentrations of selenium are having measurable impacts, such as negatively affecting swimming behaviours, in real-world ecosystems. In this thesis, I assessed the impacts of a selenomethionine-laden diet on the escape behaviours of the Fathead Minnow. Using kinematic analysis, I observed how fish responded to various looming threats. I exposed fish to sub-chronic periods of environmentally relevant concentrations of selenium in the form of selenomethionine-spiked diets. I achieved whole-body concentrations that approach Canadian tissue-specific guidelines for wild fish populations. In my first experiment, I used a weight drop to test the fish’s ability to respond to a mechanosenory stimulus and the performance of their fast-start response. My second experiment focused on the impacts of selenomethionine on visual acuity and how it affects visual perception of a threat. I also investigated how exposed fish would recover from any potential impacts when returned to a contaminant-free diet. My results indicated there was no significant effect of selenomethionine on either the visual response to a threat, or burst swimming behaviours of the fast-start response in Fathead Minnows. Additionally, there were no latent changes to Fathead Minnow escape behaviour throughout the recovery period. These results were contrary to both my predictions and the literature that showed critical swimming behaviour was compromised in selenomethionine -exposed freshwater fish. My work helps to show that the effects of toxicants on behaviours can be highly specific and cannot be generalized.
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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 | 0.001 |
| 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".