Evaluation of Microalgae for Secondary and Tertiary Wastewater Treatment
Bibliographic record
Abstract
In this study, use of microalgae for secondary and tertiary wastewater treatment was evaluated.First phase of the study investigated the ability of microalgae to remove nutrients, organic carbon and indicator bacteria from secondary effluents and centrate.For secondary wastewater and centrate, the reductions in soluble concentrations of total nitrogen, phosphorus, and COD were 27, 51.7, 29.5% and 49.4,78.6.32.8%, respectively.Total coliform reduction was greater than 99.5%.The second phase investigated the use of microalgae in combination with activated sludge system.Soluble COD removal improved from 1.5% for sample A (activated sludge) to 65.6 and 77.8% for samples B (activated sludge and microalgae) and C (microalgae).Ammonia was removed by 99.9% for B and C, while the removal was 46.4% for A. Total dissolved phosphorus was removed by 81.3 and 73.2% for B and C, but there was no reduction in dissolved phosphorus for A. 5.3.1Biomass growth and monitoring ................
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".