Bibliographic record
Abstract
Potable water treatment is one of the most challenging and complex systems that municipalities need to deal with considering limited resources. The average age of continuously deteriorating Canadian water supply system was 36 years and that would require 3.1 billion dollar to bring the system at satisfactory level. Operators have little attention to plant infrastructure and equipment compared to water quality and day-to-day operational activities. Water treatment plant (WTP) includes several elements, such as tanks, basins and pumps. Essential condition parameters are selected including technical, physical, environmental, and operational aspects of WTP. Data on the WTP conditions are collected from experts and consultants in this domain. The targeted experts were operators, designers, consultants, regulators and researchers across Canada and few from abroad. To determine the condition index of a WTP element, value additive multi-attribute theory (MAUT) has been used where average weights and scores are considered. It is concluded that the average condition index for settling basin ranges from 9.6 (best scenarios) to 1.9 (worst scenarios) and from 9.6 to 3.4 for pumps of WTP. Analysis reveals that, for tank and basins, design and construction stage is the most important parameter to the WTP condition. On the contrary, operational parameter is the most important for pumps. The study also highlights durability issues and details in structural design as the most important parameters for future condition of tanks and basins. However, operation and maintenance practice are the most important parameters for pumps.
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.
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 | 0.000 | 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 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".