Current Land and Waterborne Geophysical Methods for Guiding Horizontal Directional Drilling and Trenching Along Pipeline Right-of-Ways
Bibliographic record
Abstract
In Western Canada, oil and natural gas pipeline projects are being considered that will move hydrocarbons from the Prairie Provinces and British Columbia, to the Pacific Ocean, the Atlantic, and even potentially the Arctic. Along the proposed right-of-ways, the pipeline engineers will encounter challenging and varied terrain, including discontinuous permafrost, creek and river crossings, glaciomarine clays, thick muskeg, and other subsurface conditions that require specialized engineering planning in advance of construction. Geophysical surveys, in support of geotechnical investigations, provide continuous subsurface information to help inform design challenges associated with the many terrain challenges. Some geophysical surveys to be considered include electrical resistivity tomography (ERT), induced polarization (IP), seismic refraction, seismic reflection, multi-channel analysis of surface waves (MASW), ground penetrating radar (GPR), and borehole geophysics. Typically, a combination of several geophysical surveys along with drilling information, are optimal for the cost-effective site characterization of problematic segments of proposed pipeline right-of-ways.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".