Evaluating satellite and in situ monitoring technologies for leak detection and response
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The California Energy Commission funded a study to evaluate two technologies to assess their usefulness as an early leak detection tool for alerting field teams and to better understand the impact on energy savings through managing water loss. Specifically, the latest in advanced correlating continuous acoustic monitoring and satellite imagery leak detection technologies were examined over a period of 12 months in the Duarte system of California with 4.9 mgd production capacity and representing several pressure zones in the service area. A key conclusion was that both technologies improved the effectiveness of locating subsurface leaks that would have been invisible to the casual observer, and both were potential candidates for future applications. When implemented together in this study, the two technologies found leaks that would have resulted in between 57–170 mil gal of lost water during the study period. This equates to 140–419 MWh of energy savings in California, amounting to cost savings of at least $100,000 for the Duarte system alone during the 12‐month study period.
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.
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 | 0.001 | 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 it