Frost heave and northern pipelines, state of the art and status of research - three contributing studies
Bibliographic record
Abstract
Three review studies were conducted in response to the renewed interest in building a large diameter buried chilled natural gas pipeline in the Mackenzie Valley, Northwest Territories, to transport gas from the Beaufort/Mackenzie Delta to southern markets. The 3 review studies were commissioned by the Geological Survey of Canada to document the current state of knowledge about frost heave theory, testing and predictive modelling. The usefulness of this knowledge to the design, construction and operation of a buried chilled gas pipeline was also evaluated. The studies addressed one of the primary technical and engineering design issues that must be considered in the design of northern pipelines, that of the development of a frost bulb around buried chilled pipelines, and the associated heave of frost-susceptible soil and stresses imposed on the pipeline. The issue of differential heave is of particular concern. The information gathered from this study can be used to form the basis for the regulatory review process. This open file report provides a summary of the 3 studies. The 3 individual commissions reports were catalogued separately for inclusion in this database. refs., tabs., figs.
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 | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".