The derivation of water quality criteria for nonylphenol considering its endocrine disrupting features
Bibliographic record
Abstract
Nonylphenol (NP) is an endocrine disruptor and causes feminization in various organisms. This study aims to determine the water quality criteria for NP in China based on species sensitivity distribution (SSD) models considering both reproductive and traditional toxicity effects. A total of 17 chronic values with reproductive endpoints and 14 chronic values with traditional endpoints tested with aquatic species resident in China were found in published literature, among which six values were from marine species. As chronic toxicity data for marine species were limited, the acute-to-chronic toxicity ratio methodology was employed to extrapolate from acute-to-chronic toxicity values. The SSD models were then built with a whole set of chronic toxicity values for NP. Based on model simulation, the chronic water quality criterion in fresh water was calculated as 1.37 μg/L and 4.29 μg/L for reproductive endpoints and traditional endpoints, respectively. The criterion in seawater was derived as 1.68 μg/L for traditional endpoints. Although these criteria were derived by a third-party organization not affiliated with the Chinese authority for criteria development, they were obtained from a scientific point of view and can be used to evaluate water quality and ecological risks of nonylphenol in various water bodies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".