Uncovering transformation products of four organic contaminants of concern by photodegradation experiments and analysis of real samples from a local river
Bibliographic record
Abstract
In this study, photodegradation experiments simulating the exposure conditions of sunlight on the commonly detected in surface and wastewater contaminants atorvastatin (ATV), bezafibrate (BEZ), oxybenzone (OXZ), and tris(2-butoxyethyl)phosphate (TBEP) were conducted as the fate of these compounds and their transformation products (TPs) was followed. Then a nontargeted analysis was carried out on an urban river to confirm the environmental occurrence of the TPs after which the ECOSAR software was used to generate predicted effect levels of toxicity of the detected TPs on aquatic organisms. Five TPs of ATV were tentatively identified including two stable ones at the end of the experiment: ATV_TP557a and ATV_TP575, that were the product of hydroxylation. Complete degradation of OXZ was observed in the experiment with no significant TP identified. BEZ remained stable and largely undegraded at the end of the exposure. Five TPs of TBEP were found including four that were stable at the end of the experiment: TBEP_TP413, TBEP_TP415, TBEP_TP429, and TBEP_TP343. In the nontargeted analysis, ATV_TP557b, a positional isomer of ATV_TP557a, ATV_TP575 and the 5 TPs of TBEP were tentatively identified. The predicted concentration for effect levels were lower for ATV_TP557b compared to ATV indicating the TP is potentially more toxic than the parent compound. All the TPs of TBEP showed lower predicted toxicity toward aquatic organisms than their parent compound. These results highlight the importance of conducting complete workflows from laboratory experiments, followed by nontargeted analysis to confirm environmental occurrence to end with predicted toxicity to better communicate concern of the newfound TPs to monitoring programs.
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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 | 0.000 |
| 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".