Interpreting displacement data from complementary slope monitoring systems in extreme weather conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT As costs decrease for displacement monitoring radar units, open-pit operations increasingly incorporate multiple monitoring systems to track displacement of pit walls. At the Teck Resources Ltd. steelmaking coal operations in British Columbia and Alberta, Canada, a common practice is to couple a radar system with the installation of survey prisms. The two systems work in different ways and provide more continuous monitoring of displacement when one system is adversely affected by the punishing weather conditions at the mining operations. While there are circumstances when results from one system can be discounted, there are often instances when results from either system cannot be ignored even though they are suspect. This paper presents a methodology to evaluate results in such circumstances. It links the monitoring system status, pit-wall displacement trends, perceived risk, and recommended course of action in a manner that addresses the uncertainty of results from one or both systems.
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.
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 it