Treatment of wastewater from a school in a decentralized filtration system by percolation over organic packing media
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
Based on results obtained in the laboratory a WWTP composed of a septic tank and an aerated percolating filter packed with organic media was built for a school. The system can treat 18 m3 d(-1) and was operated with a hydraulic loading rate of 0.078 (m3 m(-2) d(-1). For 360 days different operational conditions including start-up; stabilization; operation with aeration and non aeration; effect of rainy season, breaks from activities due to holidays and restart; were monitored and described in the article. Once stabilized, the system was able to remove, without the need for mechanical aeration, 97% of BOD5, 71% of COD, 93% of TKN, 11% of PO(4-)-P, 95% of TSS, 96% of VSS, in addition to having a removal efficiency of 4 log units of Faecal Coliforms (FC) and 100% helminthes eggs (HE). With this quality, the treated wastewater can be chlorinated and reused to irrigate green areas and/or in toilets. Although sanitary wastewater has a high concentration of Total-N (250 mg L(-1)) and a C/N ratio of less than 1, the system removed 65% of Total-N. Finally it was observed that after non activity periods, there was neither system failure nor the need to re-stabilize the system.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it