DGPS LEVELLING AND MONUMENT STABILITY AT 70 ° NORTH
Bibliographic record
Abstract
The International Polar Year and the proposed development of the Mackenzie Delta gas reserves will focus attention on Arctic observation in the coming years. Methods of geodetic observation will be used alongside other scientific experiments to determine the effects of man-made and global warming changes to the environment, which will have impacts on civil infrastructure, and geological and ecological conditions. Changes in elevation are indicative of subsidence due to gas extraction, deepening of the permafrost active layer, the thawing of ground ice, and changes in the eco-system. The challenges of measuring elevation change in such a remote area, where there are few naturally stable areas or artificial benchmarks such as tide gauges, and where observations utilising conventional methods are hampered by the complex hydrol-ogy in the Mackenzie Delta, ensure the pre-eminence of global positioning in this area. Differential GPS (DGPS) levelling has its own unique challenges at 70º North, such as degraded satellite geometry and increased ionospheric effects. In addition, the full error budget of a DGPS method includes the signal of the survey monument in the permafrost environment, which is subject to seasonal heave and settlement. This paper reports on two studies that, combined, indicate the accuracy that can be expected using DGPS levelling onto survey monuments in permafrost at this latitude. The Arctic regions of Canada will be subject to intense study in the coming years due to the planned production of gas in the Mackenzie Delta
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".