Bibliographic record
Abstract
The western Lake Ontario region, a traditionally perceived area of low seismic risk, is densely populated and is home to, among other critical facilities, the nuclear reactors of Pickering and Darlington. These and other characteristics of the region call for improved estimates of seismic hazard. Due to a lack of understanding of the causative geological sources and recurrence characteristics of the reported seismic activity, there is considerable uncertainty regarding estimated ground motion parameters, a fundamental component of seismic hazard assessments. To attempt to improve the definition of the seismic source zones and, consequently, seismic hazard assessments, the hypocentres of about 30 local earthquakes were recomputed. A new data compilation, based on the revised locations or those with the least travel-time residuals, shows that local microearthquakes (ML"3.5) generally occur along, or at the intersection of, prominent aeromagnetic or gravity anomalies. A notable seismicity trend extends in a northeast-southwest direction between Toronto and Hamilton, and is bounded by magnetic lineaments. A major geological structure, the Central Metasedimentary Belt Boundary Zone (CMBBZ), coincides with a strong aeromagnetic anomaly which extends to the northeast into the Western Québec Seismic Zone. This magnetic lineament also extends to the south, across Lake Ontario, to join the Akron (Ohio) magnetic boundary that was associated with several historical earthquakes and with a mb=4.9 earthquake in 1986. Most of the seismic events recorded instrumentally in the 20th century have occurred within a depth range of 5 to 20 km. This observation supports the correlation of local earthquakes with deep geophysical and geological features, suggesting contemporary reactivation of basement structures. This may imply that a more conservative deterministic hazard estimate is needed to verify the probabilistic approach currently used to assess seismic hazard in southern Ontario.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".