The effects of polyethylene microplastics on the growth, behaviour and cognition of juvenile convict cichlids
Bibliographic record
Abstract
Microplastics, plastic particles between 0.0001 and 5 mm in diameter, are ubiquitous in the environment and are known to be consumed by organisms, leading to a variety of adverse effects. Our current study focused on identifying the effects of microplastic consumption on the growth, foraging and competitive interactions of juvenile convict cichlids (Archocentrus nigrofasciatus) and its effects on their behavioural decision making. We manipulated the levels of microplastic consumption among cichlids by feeding them brine shrimp (Artemia spp.) exposed to different concentrations of virgin polyethylene microspheres. Cichlids were exposed to microplastics for 10 days, during which we analyzed their foraging behaviour and competitive aggression during days 1, 6 and 10 of the experiment. Additionally, we measured their growth by mass. Following the 10-day exposure, we measured exploratory behaviour in a simple maze trial by quantifying latency to exploration, maze completion and shoaling. We performed the maze trial across two days and assessed differences in these metrics to make inferences on their learning ability. Initially, we found no impacts of microplastic exposure on foraging rate, growth, and competitive aggression. In contrast, we found significant effects on exploratory behaviour and maze performance. Fish exposed to microplastics exhibited higher latency to exploration, lower rates of maze completion and a larger change in their behaviour on the second day. Our current results show that virgin polyethylene microplastics at non-lethal levels have consequences on cichlid behaviour and cognition but not growth.
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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".