Simultaneous organic matter removal and nitrification of an inert self-supporting immersed media to upgrade aerated lagoons
Bibliographic record
Abstract
Abstract A pilot study was performed to evaluate the potential of an inert self-supported immersed fixed film media to upgrade aerated lagoons. Simultaneous organic matter removal and nitrification was assessed under different loading rates and temperatures (near 0 °C) using 12 laboratory-scale reactors operated in parallel. Test results showed that both the temperature and the load have an influence on organic matter effluent concentrations. Effluent quality seemed related to the observed biofilm thickness. Thicker biofilm is believed to have contributed to biomass detachment and increased particulate organic matter concentrations in the effluent. Simultaneous organic removal and nitrification was obtained at loads above 5 g CBOD5/m2·d. The highest nitrification rate at 0.4 °C was obtained for the smallest load, which showed a nitrification limitation close to freezing point.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".