Modelling the fate of polybrominated diphenyl ethers (PBDEs) during the municipal sewage treatment process
Bibliographic record
Abstract
Sewage treatment plants (STPs) are an important source to the environment for many chemicals of concern (COCs). Polybrominated diphenyl ethers (PBDEs) are one such group of COCs of present day concern for which studies on fate and transport during the STP process are limited. Availability of robust and well-tested STP models is useful in the quantification of environmental loadings and associated risk from STP discharges. In the present study, one such model (STP model) has been tested on monitoring data collected at a full-scale STP for five congeners of a commercial PBDE technical mixture. Results show that the observed trend of chemical removal and concentrations at various stages of the sewage treatment process were well simulated by the STP model for all five PBDE congeners. Continued development and evaluation of the model should continue in the future to improve its reliability and expand its applicability to a larger universe of COCs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".