Long-term geoelectrical monitoring of landslides in natural and engineered slopes
Bibliographic record
Abstract
Abstract Developments in time-lapse electrical resistivity tomography (ERT) technology are transforming our ability to monitor the subsurface due to purpose-built monitoring instruments, advances in automation and modeling, and the resulting improvements in spatial and temporal resolution. We describe the development of a novel ERT-based remote monitoring system called PRIME that integrates new low-power measurement instrumentation with data delivery, automated data processing and image generation, and web-based information delivery. Due to the sensitivity of ERT to hydrologic processes in the near surface, we focus on the application of PRIME for moisture-driven landslide monitoring. Case examples are considered of landslides in engineered and natural slopes, including those impacting geotechnical assets in rail and highways, where slope hydrology is seen to be controlled by lithology, vegetation, fissuring, and drainage structures. We conclude by taking a forward look at emerging developments in ERT monitoring relating to hardware, software and modeling, and applications.
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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".