Engineering Solutions for the Stabilisation of a Hill Located in an Urban Area. Case Study: Las Cabras Hill, Duran-Ecuador
Bibliographic record
Abstract
For more than 20 years, problems related to erosive processes and landslides have been detected on Las Cabras hill in Duran, Ecuador. Las Cabras hill has a stability problem due to its sub-vertical slopes (north zone) due to rockfalls, slopes with a favourable slope to landslide (south zone) and two anthropic factors (houses in inappropriate places and a lack of sewer system). From previous studies, Las Cabras has been classified as high to very high susceptibility to landslide (soil) or detachment (rock). Therefore, there is a risk for families living in this area and its surroundings. This study aims to propose engineering solutions through the technical considerations of studies carried out to stabilise the Las Cabras hill and its surroundings. The methodology considers: i) analysis of the results of the engineering studies carried out on the hill, ii) design calculations according to the stability and safety analysis of the slopes employing Hoek and Bray method; and iii) proposal of stabilising solutions in the most susceptible areas of the hill. The solutions have to do with controlling erosive processes and rock masses that can slide or detach. Injected anchors (using gunite and Ø25mm rods) and mechinal drains are proposed to reduce pore pressure in that area. Also, it can be applied in combination with surface channels in the form of a ladder to evacuate rainwater. Ultimately, it is possible to rethink the territorial ordering on Las Cabras hill with these considerations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".