Can glacial isostatic adjustment modelling confirm potential signs of glacially triggered faulting in Canada?
Bibliographic record
Abstract
<!--!introduction!--> Glacial isostatic adjustment (GIA) leads to remarkable stress changes in the subsurface which can be potentially released along favourably orientated pre-existing fault structures, a process nowadays termed glacially triggered faulting. A notable vertical shift of some meters can occur. In coastal areas this can affect the measured elevation of relative sea level markers. In such case these markers must be corrected before they can be used in palaeo-sea level investigations. Compared to Fennoscandia, the vast area of Canada does, so far, not contain any prominent traces of glacially triggered faulting which has led to interesting speculations in the literature. We will briefly review any suggested glacially induced faults in Canada and then analyze GIA-induced stress changes from a 3D finite element model of North America. We thereby test different stress regimes and (hypothetical) fault configurations to identify the most plausible fault parameters for reactivation. We will highlight the best parameter combinations for each fault or location of concern and compare them to available field observations. We will show that glacially triggered faulting has very likely affected most parts of Canada, including intraplate areas and Arctic islands. One example suggests that some relative sea level markers should be carefully used because faulting may have shifted the sample to a new elevation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".