CANADIAN STRONG MOTION MONITORING AND DATA ACCESS
Bibliographic record
Abstract
Strong motion monitoring across Canada involves numerous organisations. This article summarises the current state (and near-future plans) of strong motion monitoring across Canada and provides information on how to access these data. As of January 2023, the Canadian National Seismograph Network (CNSN) upgrade has been completed. As a part of this upgrade, more than 100 new strong motion instruments (Nanometrics Titans) were deployed at bedrock sites (co-located with weak motion broadband instruments) in high seismic hazard regions of Canada. In addition, 23 stand-alone strong motion instruments were deployed. A major ongoing initiative that will contribute to strong motion monitoring across the country is the deployment of the national Earthquake Early Warning network (led by Natural Resources Canada (NRCan)) that utilises strong motion instruments (Guralp Fortimus and Nanometrics Titans). As of January, 2023, 100+ strong motion instruments have been deployed with an additional 200+ strong motion instruments to be deployed across Canada over the coming year. These instruments are concentrated in the regions of high seismic risk in southwest British Columbia and southwestern Quebec/eastern Ontario. Other organisations collecting strong motion data include BC Hydro (with ~100 strong motion instruments at dam sites and substations across BC), the BC Ministry of Transportation and Infrastructure (BCMOTI) operates the British Columbia Smart Infrastructure Monitoring System (BCSIMS) which includes 100 strong motion sensors and over 400 earthquake sensors installed on 14 BCMOTI owned key bridges. In addition, Ocean Networks Canada has 11 strong motion instruments on the seafloor west of Vancouver Island and 28 strong motion instruments onshore Vancouver Island, and UBC operates dozens of instruments in southwest BC. In eastern Canada, several organisations operate strong motion instruments, including: Hydro-Quebec at dams and substations; Ontario Power Generation and New Brunswick at their nuclear power stations; PWGSC at Parliament Hill; and Gaz Metropolitain at its Montreal LNG plant. Data access is becoming easier - CNSN data are available via NRCan’s FDSN server (currently in beta-testing) at https://earthquakescanada.nrcan.gc.ca/fdsnws/ BCSIMS network data (including BCMoTI and some UBC data) are available via www.bcsims.ca and most ONC strong motion data (OW/NV networks) can be accessed via http://ds.iris.edu/ds/.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 0.020 |
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".