Reproductive Steroid Responses in Fish Exposed to Pulp Mill Condensates: An Investigation of Cause Case Study
Bibliographic record
Abstract
Abstract An investigation of cause (IOC) approach integrating artificial stream exposures and laboratory bioassays has been used to identify waste stream sources of contaminants at the Irving Pulp & Paper Ltd. mill, in Saint John, New Brunswick, Canada. Chemical recovery condensates have shown the greatest potential for reducing circulating steroids in mummichog (Fundulus heteroclitus), an endemic fish species. A solid phase extraction (SPE) technique was developed to isolate hormonally active substances from the condensates, and a toxicity identification evaluation approach was used to gain a better understanding of the chemical characteristics of the active substances. Extracts were fractionated by high performance liquid chromatography (HPLC) and the fractions were used in a seven-day bioassay. Dose-response experiments indicated that steroid reductions in male mummichog were observed consistently after a 4% (vol/vol) exposure. At 4% (vol/vol), however, steroid reductions were not observed in fractions of the active SPE extract generated by HPLC. Some fractions actually induced increases in plasma testosterone. Recent work has focused on understanding what methodologies must be used to handle the semivolatile condensates to ensure 100% chemical recovery and retention of biological activity. Results are summarized in the context of developing an industry-wide IOC framework.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".