Spatial and temporal variations in seismic coda Q attenuation in the lower St. Lawrence region, southeastern Quebec
Bibliographic record
Abstract
We investigate seismic attenuation characteristics of the Lower St. Lawrence seismic zone in southeastern Quebec. This zone is located ~400 km downstream from Quebec City and is between the Quebec North Shore and the Lower St. Lawrence. We used earthquake recordings from 5 broadband and 5 short period seismograph stations of the Canadian National Seismic Network (CNSN) across the region. Our dataset is comprised of 847 earthquakes recorded between 1985 and 2022 with magnitudes ranging from 2.0 to 5.1, depths from 0 to 30 km and epicentral distances of 5 to 100 km. This gives a total of 446 high signal-to-noise (S/N) traces (S/N>5.0) useful for QC calculation (with a maximum ellipse parameter, a2, of 100) across the region. Coda windows were selected to start at tc = 2tS (two times the travel time of the direct S wave), and were filtered at center frequencies of 2, 4, 8, 12 and 16 Hz. Our study reveals a consistent pattern. We find that the lowest overall average of Q0 (Q at 1 Hz) values are at the three stations (GSQ, ICQ and SMQ) within 100 km of a moderate earthquake of mN 5.1 in 1999 (e.g., Q0 of 81, 88 and 80, respectively). We determined temporal variations in attenuation following the 1999 earthquake. The overall average of Q0 decreased from 87 (before the mainshock) to 77 (GSQ, D=96 km), from 92 to 85 (ICQ, D=69 km) and from 88 to 82 (SMQ, D=73 km). These results are in agreement with global studies that show a decrease in Q0 following a significant earthquake, (e.g., M > 5) likely the result of increased fracturing and fluids in the epicentral region. An average for all the data results in a Q relationship of QC = 86f1.07 for the frequency band of 2 to 16 Hz for the entire region.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".