Persistent contaminants of emerging concern in ozone‐biofiltration systems: Analysis from multiple studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Water quality, in combination with design and operational data collected from multiple studies, was assessed to benchmark the performance of ozone‐biologically active filtration in reuse applications. A total of 149 contaminants of emerging concern, representative of multiple categories and chemical structures, were prioritized and systematically compared to elucidate apparent differences in removal capabilities as affected by multiple factors such as influent water matrix, ozone‐to‐organic carbon ratio, empty bed contact time, filtration media type, and initial media condition. The results were consistent with earlier findings for the removal of highly amenable compounds but demonstrate inconsistencies and knowledge gaps across multiple facilities for the more persistent compounds. Analysis of this multistudy data‐mining effort also demonstrates a complicated interplay between contaminant removal and numerous design and operational variables. Hence, further systematic investigation is warranted to elucidate the underlying removal mechanisms.
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.
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 | 0.001 |
| 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) | 0.000 | 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 it