The impact of alum coagulation on pharmaceutically active compounds, endocrine disrupting compounds and natural organic matter
Bibliographic record
Abstract
This study assessed the impact of chemical coagulation using alum on the removal of three endocrine-disrupting compounds (EDCs; bisphenol A, clofibric acid and estriol) and nine pharmaceutically active compounds (PhACs; acetaminophen, carbamazepine, diclofenac, gemfibrozil, ketoprofen, naproxen, pentoxifylline, sulfamethoxazole and sulfachloropyridazine). The impact on natural organic matter (NOM) fractions as determined using liquid chromatography–organic carbon detection (LC–OCD; total dissolved organic carbon (DOC), hydrophobic DOC, biopolymers, humic substances, building blocks, low molecular weight neutrals and acids) was also examined. Three test surface waters were included: Lake Ontario, Grand River and Otonabee River water (Ontario, Canada). Gemfibrozil concentrations were reduced in both Otonabee and Grand River waters. Reductions were noted for carbamazepine and (inconsistently) for acetaminophen, and estrone appeared to increase in concentration in Grand River water with increasing alum doses. NOM removal was primarily attributed to the humic fraction, with small reductions in biopolymers in all of the waters studied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".