Results from a Comprehensive 2022 Study of Water Main Performance in the USA and Canada
Bibliographic record
Abstract
Utah State University (USU) has just completed the most comprehensive water main survey ever undertaken in the US and Canada for the purpose of understanding how utilities use pipe in their systems and determining the performance of different pipe materials. Of the 802 basic survey respondents, 791 participants provided water main distribution data having a total of 399,812 mi of pipe. This pipe mileage represents 17.1% out of an estimated 2.33 million miles of pipe that is installed in the US and Canada, making this the largest survey of its kind. A full USU report of these most recent survey results was published in December of 2023. Similar survey results were published by USU in 2012 and 2018. When the most common pipe materials (cast iron, ductile iron, PVC, and asbestos cement) were compared, PVC had the lowest overall failure rate and cast iron had the highest at 2.9 and 28.6 breaks (100 mi-year), respectively.
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) | 0.001 | 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".