Bibliographic record
Abstract
‘Net Positive Water’ explores the capability of domestic architecture to combat the developing urban water problem. Urban intensification is contributing to the volatility of urban waters and the breakdown of the urban water cycle. Inhabitant water misuse and overconsumption is overwhelming aging municipal utilities, resulting in the decay of urban water quality. \n \nLEEDTM and The Living Building Challenge are recognized Green Building Guidelines prescribing sustainable site and building water standards. Case Studies of domestic Green Building projects will showcase water conservation to enable domestic water renewal. Net Zero Water Guidelines based on the Green Building Guidelines outline \nPotable and Non-Potable water use to achieve a sustainable volume of water demand at 70 litres per capita per day. Sustainable water practices are encouraged by utilizing domestic building systems to increase water \nvalue and water awareness. Time-of-Use and Choice-of-Use exposure for household water related tasks establish water savings through the use of best-performing water fixtures and appliances. \n \nNet Positive Water Guidelines will establish On-site and Building standards for sustainable harvesting and storage of water resources. Clean and Dirty water management will prescribe Passive design and Active mechanical processes to maintain best-available water quality in the urban domestic environment. Net Positive Water building typology will integrate urban inhabitation as a functional component of the urban water cycle to use, reuse, and renew water resources. The method will be \ntested using a Mid-rise Pilot project to deploy the necessary Passive and Active mechanisms to generate Net Positive Water quality through Net Zero Water sustainable water use. The pilot project is situated in \nWaterfront Toronto - The Lower Don Lands development to harness regional interests for water renewal and environmental revitalization.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.223 | 0.057 |
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".