Case Studies in Landslide Repair along Coastal and Riparian Areas
Bibliographic record
Abstract
Landslides along our nation's waterways can present a real challenge to engineers, planners and designers. Many of the common tools available either present a large environmental impact or are not robust enough to handle the corrosion, scour, rapid drawdown, and wave action associated with riparian and coastal sites. Through four case studies from riparian/coastal projects across the United States (a coastal bluff erosion project using fiberglass soil nails near Crescent City, California; a landslide repair using launched drainage nails in Saskatchewan, Canada; a riparian landslide repair in Virginia using battered micropiles; and a lakeshore landslide repair along Lake Tahoe, California) new and innovative erosion control and landslide mitigation tools are presented. Those include soil nailing, high capacity tensioned wire mesh with vegetative mats, reinforced geologically sculpted shotcrete, scour micropiles, and fiberglass composite ballistic soil nails/horizontal drains.
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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".