Site corrections and residual analysis for seismograph stations used for magnitude calculations in eastern Canada
Bibliographic record
Abstract
Earthquake magnitudes are generally determined by taking an average (most often, the arithmetic mean) of magnitudes calculated at many individual seismograph stations. While some variation in station magnitudes stems directly from the seismic source (for example, radiation pattern or directivity) conditions beneath the recording station also affect the calculated value. For example, soft soils tend to amplify the seismic signal resulting in an apparent magnitude that is higher than the true value. By analyzing the differences between the magnitude determined at a specific station and the average magnitude for a large number of earthquakes, a site correction for the station can be determined and then applied as part of the magnitude calculation. Station corrections have been determined for more than three hundred seismographs used in the calculations of magnitudes in eastern Canada. In most cases, the site corrections are small but several stations with significant corrections were identified. Magnitudes were recalculated applying the corrections. When the earthquake catalog is considered as a whole, the effect is negligible but there are many individual earthquakes for which it is significant. The remaining residuals after the application of the site corrections were further evaluated to determine whether they are dependent on parameters such as distance, azimuth or frequency. A consistent pattern of residuals with respect to distance is seen at a large number of stations spanning the region, suggesting that the attenuation relation used in magnitude calculations may need to be modified. In most regions azimuthal dependence is minimal but a few regions have been targeted for further study. Residuals are near zero for periods of ~0.02 - ~0.5 sec and then slowly increase with increasing period, raising questions about the validity of using the magnitude equation over a wider range of frequencies than that for which it was originally intended.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| 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".