GPS crustal strain, postglacial rebound, and seismic hazard in eastern North America: The Saint Lawrence valley example
Bibliographic record
Abstract
We present Global Positioning System (GPS) measurements that constrain the amplitude, pattern, and origin of crustal deformation in the Saint Lawrence valley, Québec, one of the most seismically active regions of eastern North America. The GPS network shows coherent southeastward motion of 0.6 ± 0.2 mm yr−1, relative to North America, and uplift of 2.6 ± 0.4 mm yr−1. Network average horizontal strain rates are mostly ESE‐WNW shortening at (1.7 ± 1.0) × 10−9yr−1. The shortening rate across the Charlevoix seismic zone is about twice as big as the regional average. These measurements are consistent with both postglacial rebound (PGR) models and the deformation style indicated by earthquake focal mechanisms. Although the GPS data do not discriminate between various models of crustal deformation, they provide important constraints on large earthquake recurrence. Assuming that the GPS strain estimates are representative of seismic moment release, they constrain the maximum magnitude of truncated Gutenberg‐Richter recurrence statistics in the Charlevoix seismic zone toMX= 7.8 ± 0.6 (oneM≥ 7 earthquake per 400–1300 years). The remarkable agreement between the GPS strain rates, seismic catalogue statistics, and PGR predictions suggests that in Charlevoix, most of the PGR‐driven crustal strain may be released by large (M≥ 7) earthquakes. In the rest of the Saint Lawrence valley, PGR strain rates are significantly larger than seismic strain rates, suggesting either that PGR deformation remains mostly elastic or that large events are more frequent than indicated by small earthquake statistics (i.e., characteristic earthquakes).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".