Transformation products of contaminants of emerging concern in water by UV-based processes
Bibliographic record
Abstract
Abstract Contaminants of emerging concern (CECs) and their respective transformation products (TPs) formed following photodegradation pose considerable threats to the environment and our health. The formation of TPs during UV-LED-based degradation of three target pollutants in the EU Watch List of CECs was accessed by LC-MS-Orbitrap, and their reaction pathways were elucidated. The influence of different matrices and treatments of choice on TP formation was investigated. Results showed that matrix changes did not produce different reaction pathways during UV-A photocatalysis, although plots of TP peak areas vs. time were different for each case. A new TP was found for the antidepressant venlafaxine, (1-[2-(dimethylnitroryl)-1-(4-methoxyphenyl)ethyl]cyclohexanol. When comparing UV-A photocatalysis with UV-C photolysis, dissimilar pathways were observed due to the distinct reaction mechanisms of each process, since photocatalysis, unlike photolysis, relies on radical-based reaction routes. Different levels of confidence were obtained for each TP depending on the availability of MS2 data in the literature and of standards for comparison. All the found TPs had similar molecular masses in comparison to their respective parent compounds. Most of the TPs remained in the effluent after 6 hours of photodegradation, which highlights the importance of their control, close-monitoring, and further toxicity assessments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".