Bibliographic record
Abstract
Weather-related geo-hazards are a major concern for both natural slopes and man-made slopes and embankments. Government agencies and private companies are increasingly required to ensure that there is adequate protection of sloping surfaces in order that interaction with the climate does not produce instability. Superior theoretical formulations and computer tools are now available to address engineering design issues related to the near ground surface soil-atmospheric interactions. An example is given in this paper that illustrates the consequences of not paying adequate attention to the hazards of slope stability prior to the construction of a highway in South America. On the other hand, examples are given from Hong Kong and Mainland China where significant benefits are derived from putting in place a hazard slope stability management system. Some results from a hazard management slope stability study related to the railway system in Canada are also reported. The study took advantage of recent research on unsaturated soil behaviour and applied this information to real-time modelling of climatic conditions. The quantification of the water balance at the ground surface, and subsequent infiltration, is used as the primary tool for hazard level assessment. The suggested hazard model can be applied at either specific high risk locations or in a more general, broad-based manner over large areas. A more thorough understanding of unsaturated soil behaviour as it applies to near ground surface soils, along with the numerical computational power of the computer has made it possible for new approaches to be used in slope hazard management engineering.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".