Modeling the adsorption of emerging contaminants on activated carbon: classical and quantum QSAR approaches
Bibliographic record
Abstract
The adsorption of 115 emerging contaminants, mainly organic chemicals identified by the US Environmental Protection Agency's 2009 Contaminant Candidate List 3, was ranked using two published classical quantitative structure-activity relationship (QSAR) models and a newly developed quantum QSAR model. Approximately 75% of the investigated contaminants were predicted to be cost-effectively treatable, with an activated carbon usage rate below 10 mg/L. A limited experimental validation campaign was carried out by rapid small-scale column testing (RSSCT) using Lake Ontario water for eight selected compounds: 17β-estradiol, ibuprofen, diazinon, sulfamethoxazole, carbamazepine, 4-nonylphenol diethoxalyate, azithromycin and tylosin, with the activated carbon adsorption of the latter three having never been previously reported. The experimental results were consistent with the quantum chemistry model rankings.
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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 | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".