Impacts of caffeine on fathead minnow behaviour and physiology
Bibliographic record
Abstract
Pollution from regularly used substances such as pharmaceuticals, cleaning agents, and even food and beverages is an increasing problem in the environment. Caffeine, a commonly ingested stimulant, is one such contaminant that has been detected in aquatic environments worldwide. Yet, little is known about how ecologically relevant concentrations of caffeine influence the morphology, behaviour, and physiology of exposed organisms. To address this knowledge gap, we exposed fathead minnow (Pimephales promelas) to three caffeine treatments: a freshwater control (nominal: 0 ng/L), a low (nominal: 1,000 ng/L) and high environmentally relevant dose (nominal: 10,000 ng/L), for 35 days. We tested the learning abilities, anxiety, metabolic rates, and morphological features of exposed vs. control fish. Caffeine exposure did not affect the ability of fish to learn but did influence anxiety levels. Over the course of repeated anxiety testing, unexposed control fish visited a black square more often while fish exposed to low levels of caffeine did not, potentially indicating that these fish remained in a more anxious state. While caffeine did not impact metabolism, fish growth, or body size, it was associated with lower liver investment-although this response was only observed in our low caffeine treatment. Overall, our results suggest that even relatively low concentrations of caffeine may impact the liver size and anxiety of exposed fish, but further research is needed to assess how extended exposure to caffeine impacts fitness. Given the increase in anthropogenic contaminants in aquatic environments, it is important that we continue to investigate their effects on the organisms exposed to them.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".