Anchor Bars in Frozen Bedrock - Curing Techniques for Backfill Grout
Bibliographic record
Abstract
As part of a power plant expansion project at the Diavik Diamond Mine in the Northwest Territories of Canada, forty eight (48) rock anchors for six (6) exhaust stack foundations were designed, installed and pull-tested. The Diavik Diamond Mine is located in a region of continuous permafrost which presents unique challenges for design and construction. In particular, frozen bedrock is known to slow the curing time of grout, and if incorrectly cured, significantly reduce the strength of the cured grout. In an effort to accurately replicate the in-situ ground temperature conditions while curing grout samples, single node thermistors were installed to monitor ground temperatures and the samples of the cold weather anchor grout were cured in a calcium chloride ice-bath. The anchor installation procedure, cold weather anchor grout formulation, in-situ ground temperature measurements, unconfined compressive strength (UCS) test results of the ice-bath cured grout and a summary of the anchor pull-test results are presented.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".