Construction, Operation and Evaluation of a Compact Upright Bioreactor for the Elimination of Nutrients (CUBEN)
Bibliographic record
Abstract
Eutrophication is reported as the most important water quality issue around the world. The potential death of Lake Winnipeg, the world's ninth largest lake, is a dramatic exampe of this ecological disater in Canda. Property price devaluation, tourist repulsion, and toxicity due to eutrophication cause the annual economic losses over $3 billion in Europe, South and North America. The objective of this thesis is to develop an efficient biological nutrient removal reactor to be commercialized and used in the water/wastewater treatment industry. This bioreactor has a unique configuration which is filed as a US patent technology called "Compact Upright Bioreactor for the Elimination of Nutrients", invented by M. Alvarez Cuenca and M. Reza. It consists of four stages including Deaeration, Anoxic, Anaerobic and Aerobic where Do removal, denitrification and phosphorus removal processes take place respectively. The bioreactor performs very well obtaining 100% Do removal and 98% nitrate removal efficiency. The phosphorus removal process requires much longer operational period to reach steady state. The phosphorus removal process shows variable results having a maximum of 60% removal success.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".