Estimation of influent concentrations of estrogens and select prescription drugs in wastewater treatment plants
Bibliographic record
Abstract
Due to the high costs associated with laboratory analysis, load estimation of pharmaceuticals is necessary to identify compounds that may have high influent and effluent concentrations in wastewater treatment plants (WWTPs). The load estimation model presented in this paper was developed to estimate the influent concentration of prescription and over-the-counter (OTC) drugs in WWTPs. It accounts for the demographic profile of the population served by the WWTP and was based on a previous estimation model for estrogens. The model was applied to: 1) two statin compounds prescribed for lowering cholesterol levels, and 2) acetaminophen, an OTC drug for pain relief. The previous estrogen model was also used, with minor modification to conform to our proposed model, to estimate the influent concentration of 17-β estradiol in two medium-scale WWTPs. Differences between model predictions and actual measured concentrations ranged from 1.2% to 130%, suggesting model calibration is needed to improve reliability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".