Effect-Directed Analysis of Aryl Hydrocarbon Receptor Agonists in Sediments from the Three Gorges Reservoir, China
Bibliographic record
Abstract
The construction of the Three Gorges Dam (TGD) in the Yangtze River raises great concern in ecotoxicological research since large amounts of pollutants enter the Three Gorges Reservoir (TGR) water bodies after TGD impoundment. In this work, effect-directed analysis (EDA), combining effect assessment, fractionation procedure, and target and nontarget analyses, was used to characterize aryl hydrocarbon receptor (AhR) agonists in sediments of the TGR. Priority polycyclic aromatic hydrocarbons (PAHs) containing four to five aromatic rings were found to contribute significantly to the overall observed effects in the area of Chongqing. The relatively high potency fractions in the Kaixian area were characterized by PAHs and methylated derivatives thereof and heterocyclic polycyclic aromatic compounds (PACs) such as dinaphthofurans. Benzothiazole and derivatives were identified as possible AhR agonists in the Kaixian area based on nontarget liquid chromatography-high resolution mass spectrometry (LC-HRMS). To our knowledge, this study is the first one applying the EDA approach and identifying potential AhR agonists in TGR.
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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 | 0.001 | 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) | 0.000 | 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 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".