Effects of point‐source discharges on shortfin eels ( <i>Anguilla australis</i> ) along the Waikato River, New Zealand
Bibliographic record
Abstract
ABSTRACT The Waikato River is the longest river in New Zealand and is exposed to range of anthropogenic stressors. This study investigated the effects of three major point‐source discharges on resident shortfin eels Anguilla australis along the river. Shortfin eels were caught from sites upstream and downstream of discharges of bleached kraft mill effluent (BKME) from pulp and paper manufacture, sewage, and a thermal power plant. At each site, population parameters (relative abundance and age structure) and individual metrics of health such as condition factor and organ (gonad, liver, and spleen) to somatic weight ratios were measured. Blood, biochemical (hepatic 7‐ethoxyresorufin‐ O ‐deethylase or EROD) and chemical markers (bile chemistry and trace elements in flesh) were also measured. Measures of exposure and response to discharges confirmed that the shortfin eels were resident at the sites sampled. The discharges had few negative impacts on individual eel health and positive responses were seen to warm water discharge. However, resident shortfin eels were immature so reproductive responses could not be determined. In conclusion, shortfin eels in this study showed few responses to the effects of the discharges except for increased resin acids, bile polycyclic aromatic hydrocarbons, and EROD at the BKME site.
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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 | 0.000 |
| 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".