Developing a standard methodology for testing field performance of residential greywater reuse systems: Case study of a greywater reuse system installed in 23 homes in Southern Ontario
Bibliographic record
Abstract
Using shower wastewater to flush toilets decreases the potable water demand of residential buildings, reducing pressure on existing water supplies. “Off- the-shelf” greywater reuse systems intended for single-family residential dwellings have recently become commercially available, but have variable field performance. A standard field testing methodology was developed and applied to a greywater reuse system installed in 23 homes in Southern Ontario. Performance was quantified by measuring the water balance, water quality, energy consumption, durability, maintenance requirements, installation process, economics and user satisfaction with the system. The tested system was found to save, on average, 40.9 litres per household per day, occasionally meet water quality guidelines and generally have less maintenance and durability issues than previous generations, resulting in satisfied users. However, due to low water rates and high capital costs, there is a need for government subsidization of these systems which will ultimately, reduce pressure placed on centralized water infrastructure.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".