Instrumentation and Real Time Monitoring of a Landslide on Highway No. 302 Near Prince Albert,
Bibliographic record
Abstract
Saskatchewan Department of Highways and Transportation (SDHT) implemented a Risk Management System for the provincial highway network in 2003. The Risk Management System was developed to prioritize sites for investigation and allocate resources for construction and maintenance. The Risk Management System identified a section of Provincial Highway No. 302, approximately 4.5 km west of Prince Albert, Saskatchewan, as an urgent site requiring immediate investigation and monitoring. As of April 2006, a 420 m of the highway was dropping as a result of large retrogressive landslides along the North Saskatchewan River. Investigation and slope stability analysis indicated the remediation options were limited to the re-alignment of the highway. However, re-alignment of the highway would be costly and require time to design and construct. Daily inspection and monitoring of the site instrumentation were recommended until remedial measures could be implemented but the remote location of the site and high speed of landslide movement were not amenable to traditional means of inspection and monitoring. As a result, an automated
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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 | 0.001 | 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) | 0.001 | 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".