Removal of cyanobacterial metabolites through wastewater treatment plant filters
Bibliographic record
Abstract
Wastewaters have the potential to proliferate excessive numbers of cyanobacteria due to high nutrient levels. This could translate to the production of metabolites, such as the saxitoxins, geosmin and 2-methylisoborneol (MIB), which can impair the quality of wastewater destined for re-use. Biological sand filtration was assessed for its ability to remove these metabolites from a wastewater. Results indicated that the sand filter was incapable of effectively removing the saxitoxins and in some instances, the effluent of the sand filter displayed greater toxicity than the influent. Conversely, the sand filter was able to effectively remove geosmin and MIB, with removal attributed to biodegradation. Granular activated carbon was employed as an alternative filter medium to remove the saxitoxins. Results showed similar removals to previous drinking water studies, where efficient removals were initially observed, followed by a decrease in the removal; a consequence of the presence of competing organics which reduced adsorption of the saxitoxins.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".