Strong motion seismograph networks in Canada
Bibliographic record
Abstract
Strong motion monitoring in Canada has undergone significant changes in recent years. Most analogue, non-communicating instruments have been replaced with modern digital instruments that provide information in real-time. Dense networks are being deployed in the urban centres of southwest British Columbia to provide shaking parameters and "shake maps" immediately after an earthquake. Monitoring of critical infrastructure, including bridges, dam sites and transmission facilities is increasing. This article documents the current state of strong motion monitoring across Canada, and summarises the data sets that are currently available. As of 2007, the Geological Survey of Canada operates 97 strong motion instruments (all Internet Acclerometers or IA's) in western Canada, most of which are deployed in the urban centres of high seismic hazard in southwest British Columbia. BC Hydro has 39 strong motion instruments at dam sites across BC. More than half of these are analogue SMA-1's, and are scheduled to be replaced by digital instruments within 2-3 years. BC Transmission Corporation owns 23 instruments (SSA-2's and ETNA's) installed at major substations and terminal stations across southwest BC. Other strong motion instruments in western Canada are owned by utilities or transportation organisations (BC Ministry of Transportation (MoT) has deployed 17 instruments to monitor lifeline bridges and a tunnel). In eastern Canada, the GSC operates a network of 26 strong motion instruments in the active Charlevoix zone, and 11 instruments in greater Ottawa. Hydro-Québec operates instruments at 12 dams and substations. Gaz Metropolitain operates an instrument at its Montreal LNG plant and New Brunswick Power operates an instrument at the Point Lepreau nuclear station. During the past six years, nearly 700 accelerograms have been recorded across Canada. Most of the records represent weak motion (PGA less than 5%g), nonetheless, they are useful for evaluating local site response, which in turn may be valuable to engineers evaluating strong ground shaking during future 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".