Quality assurance considerations for friction rock stabilizers
Bibliographic record
Abstract
Friction rock stabilizers (FRS) are routinely used to provide rock reinforcement to excavations in hard rock. Since the expiration of the original patent taken out in 1977, FRS are now available from multiple suppliers. The expectation that all FRS are equivalent, however, is not necessarily accurate. There are inherent variations in the design configuration, material chemistry/properties, and consequently in performance. In this context, a full traceability from steel grade and heat treatment to final product is critical. This paper reports the results of a QA/QC investigation aiming to identify the material properties for three equivalent FRS from the same supplier. A series of mechanical and accelerated corrosion tests highlighted the differences in these rockbolts. This work provides a template for a more comprehensive quality assurance programme to ensure compliance of FRS. This is critical when rockbolts, due to global supply chain constraints, are outsourced from multiple sources worldwide.
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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 | 0.001 | 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) | 0.000 | 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".