The effects of changing NOM composition and characteristics on coagulation performance, optimisation and control
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
A number of water utilities have been experiencing operational difficulties during specific times of the year, associated with elevated levels of organics due to heavy rainfall or snow melt. Water samples were collected from Albert treatment works (Halifax, UK) and the natural organic matter (NOM) was characterised using XAD resin adsorption techniques. The addition of a cationic polyelectrolyte was employed to determine the charge density of the fractions. Results show that NOM fraction make-up changes throughout the year, with the fulvic acid fraction (FAF) showing the greatest increase during the autumn and winter period. The charge density of the FAF fraction also increases. The coagulation conditions for traditional coagulants, such as iron, are more affected by increased levels of organics than the novel coagulant also investigated, and the zeta potential range for optimum removal is narrower. Therefore, the conditions required for zero charge during coagulation varies with both raw water source and the coagulant type.
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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 | 0.001 |
| 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