Influence of seasonal soil temperature variation and global warming on the seismic response of frozen soils in permafrost regions
Bibliographic record
Abstract
Abstract There has been growing interest in seismic hazards in permafrost regions as development in those regions has increased. Because major infrastructure, such as natural gas pipelines, has been constructed in permafrost regions, it is necessary to evaluate the seismic safety of such a network system. As frozen soil's dynamic properties differ from those of its unfrozen state, the characteristics of seismic waves propagated through frozen soil layers in permafrost differ from those propagated through unfrozen soil. Thus, the dynamic properties and composition of frozen soil layers located between bedrock and the ground surface need to be realistically considered in evaluating the seismic hazards of permafrost regions. The frozen soil layer's composition greatly depends on soil temperatures which vary seasonally and are gradually increasing due to global warming, therefore it is necessary to consider soil temperature variation. In this study, comprehensive parametric site response analysis was carried out based on measured data regarding seasonal and annual temperature variation to investigate seismic hazards. The soil temperature variation between summer and winter and temperature increases due to global warming were the main considerations. The analysis results clearly show that the soil temperature variation significantly impacts seismic hazards in the permafrost region, leading to different site response characteristics than those in the non‐permafrost region.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".