Strain Accumulation and Release Rate in Canada: Implications for Long‐Term Crustal Deformation and Earthquake Hazards
Bibliographic record
Abstract
Abstract To advance the understanding of crustal deformation and earthquake hazards in Canada, we analyze seismic and geodetic data sets and robustly estimate the crust strain accumulation and release rate by earthquakes. We find that less than 20% of the accumulated strain is released by earthquakes across the study area providing evidence for large‐scale aseismic deformation. We attribute this to glacial isostatic adjustment (GIA) in eastern Canada, where predictions from the GIA model account for most of the observed discrepancy between the seismic and the geodetic moment rates. In western Canada, only a small percentage (<20%) of the discrepancy can be attributed to GIA‐related deformation. We suspect that this may reflect the inaccuracy of the GIA model to account for heterogeneity in Earth structure or indicate that the present‐day effect of GIA in western Canada is limited due to the fast response of the upper mantle to the deglaciation of the Cordillera Ice Sheet. At locations of previously identified seismic source zones, we speculate that the unreleased strain is been stored cumulatively in the crust and will be released as earthquakes in the future. The Gutenberg‐Richter model predicts, however, that the recurrence interval can vary significantly in Canada, ranging from decades near plate boundary zones in the west to thousands of years in the stable continental interior. Our attempt to quantify the GIA‐induced deformation provides the necessary first step for the integration of geodetic strain rates in seismic hazard analysis in Canada.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".