ShakeMap for the MN 5.4, 6 March 2005 Riviere-du-Loup, Quebec Earthquake
Bibliographic record
Abstract
Since the beginning of June 2004, near-real-time ShakeMaps have been produced in Ontario for earthquakes of M > 2.8 and are posted at http://www.shakemap.carleton.ca/ within minutes of occurrence. ShakeMaps, originally conceived by Wald et al. (1999), provide rapid online assessment of locations, shaking intensities, and expected levels of damage to specific areas, The Nuttli magnitude ( M N ) 5.4 earthquake which occurred 17 km southwest of Riviere-du-Loup, Quebec on 6 March 2005 was the first moderate, well recorded event since the implementation of the Ontario ShakeMap project. It provided a good opportunity to evaluate the performance of ShakeMap in eastern Canada. The ShakeMap location and moment magnitude, based on the ground-motion centroid, are very close to traditional estimates of these parameters. ShakeMap intensities agree with the preliminary observed intensity results collected based on felt reports submitted online. Recorded ground-motion parameters from this earthquake agree very well with the predictions of empirical ground-motion relations developed for ShakeMap applications by Kaka and Atkinson (2005a), as well as with relations developed by Atkinson and Boore (1995).
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 | 0.002 |
| 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) | 0.047 | 0.008 |
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".