Deformation Monitoring for the Assessment of Sacramento Delta Levee Performance
Bibliographic record
Abstract
The Sacramento Delta levee network plays a vital role in supporting the United States’ largest agricultural production and the municipal water supply for millions of people. Beyond the potential for earthquake-induced failure, performance monitoring of the levee system on the network level and the assessment of potential distress levels are needed for the maintenance and rehabilitation of this system. In this case, critical deformation needs to be assessed especially in view of the levees age, sea level rise, and ongoing subsidence due to the decomposition of the peat foundation layer. The work presented herein describes the remote sensing of a levee section deformation with time. The levee section is located on Sherman Island, CA, and monitoring was conducted in situ by GPS, in addition to remote sensing by airborne synthetic aperture radar and satellite systems. Coupled deformation/seepage numerical analysis of the levee section is performed using PLAXIS. The numerical model included characterization of the unsaturated-saturated zones and the peat foundation layer. Key parameters of the peat layer were synthesized from published data to provide baseline assessment for the current condition of the levee system in view of the measured rate of deformation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".