The impact of oestrogenic sewage discharges on fish \npopulations
Bibliographic record
Abstract
For the last 3 years, this multi-institute programme has been addressing the question of whether oestrogenic \ndischarges from sewage treatment plants are able to damage fish populations. It has been known for some \ntime that such discharges are able to feminise individual male fish of several species in rivers and estuaries, causing induction of various oestrogen biomarkers and altering the development of testicular tissue. It has been hypothesised that feminised (intersex) fish may be reproductively compromised, and this has been demonstrated in life cycle experiments in the laboratory. Furthermore, in vitro experiments have shown that sperm from strongly intersex male roach Rutilus rutilus has reduced ability to fertilise eggs. However, impacts of oestrogens on wild fish populations caused by treated sewage have not been demonstrated to \ndate, although an experiment in a Canadian lake treated with ethinylestradiol at environmentally-relevant \nconcentrations caused the collapse of a fathead minnow Pimephales promelas population. The programme \ndescribed in this presentation (Endocrine Disruption in Catchments – EDCAT) has tackled this issue by \nstudying wild 3-spined stickleback Gasterosteus aculeatus populations in a sewage-contaminated river, and has conducted semi-natural group-breeding experiments with R. rutilus, in which normal males have been allowed to compete with intersex fish. These studies have been supported by detailed chemical analytical and in vitro bioassay measurements, and by the development of improved oestrogen exposure models. \nThe project has focused on the River Ray in southern England whose lower reaches are largely composed \nof treated sewage effluent from the city of Swindon, and a reference river (the Ock) which is similar to the \nRay but receives far less effluent. The Ray was chosen because the Swindon sewage discharge (Rodbourne) was due to be upgraded with granular activated carbon (GAC) treatment plant in early 2008 which was expected to lead to a big reduction in oestrogenic (and other) inputs to the river. This change in inputs provided a good opportunity to study any recovery of fish populations. However, the intersex roach for the breeding experiments have been obtained from several other UK rivers including the Rivers Arun, Bourne, Aire and Nene.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".