A Critical Assessment of Canadian Earthquake Monitoring and Alerting Practice versus the Initial Challenges of the 2020 COVID-19 Experience
Bibliographic record
Abstract
Abstract We describe the regular pre-COVID mode of operations for the Canadian National Seismograph Network and the associated monitoring, alerting, and analysis for earthquakes in Canada; we describe how the current operational posture evolved and discuss the ways in which the posture was and was not suitable to respond to the challenges and constraints of the COVID-19 situation in Canada. We find that many of the design and operation decisions that have been taken over the last several decades for earthquake monitoring in Canada, collectively driven largely by considerations of resilience and cost-effectiveness and further refined after the experience of the H1N1 pandemic, resulted in a system that continued to function effectively under lockdown conditions. There were many earthquakes in Canada that required seismologist response during the lockdown, all of which were handled remotely without issue. Specific challenges and lessons learned from the first few months of the pandemic are noted.
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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 | 0.030 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".