Seismicity of the Southern Great Lakes: Revised Earthquake Hypocenters and Possible Tectonic Controls
Bibliographic record
Abstract
Abstract Using data from 27 seismograph stations for the period 1990–2001, we have relocated 106 hypocenters of earthquakes with magnitudes from 0.9 to 5.4 in the region of the southern Great Lakes. Two complementary methods were used for relocation: a conventional least-squares approach (Lienert and Havskov, 1995) and joint hypocentral determination (Pujol, 2000). These two methods yielded mutually consistent spatial patterns of seismicity with an average difference of 3.7 km in epicentral locations and 1.1 km in focal depths. We show that the hypocenter loca-tions are not very sensitive to realistic uncertainties in 1D crustal velocity. Our sharp-ened definition of zones of seismicity delineates several clusters beneath Lake On-tario, around Niagara Falls, and near the south shore of Lake Erie. These seismicity zones appear to correlate with areas where the regional magnetic data exhibit promi-nent short-wavelength (5 km) linear anomalies. The magnetic anomalies are as-sociated with basement structures that formed during the Precambrian (Mesoproter-ozoic) Grenville orogen. Both the seismicity and magnetic anomalies exhibit statistically significant preferred orientations at N40E–N45E, but the correlation of the earthquake clusters with specific aeromagnetic lineaments remains uncertain. Three preliminary focal mechanisms of earthquakes with magnitudes mN 3.1 to 3.8 show unusual normal faulting, with nodal planes in almost the same direction as the magnetic trends, N42E–N52E. Proximity of the earthquake clusters to large bodies of water, coupled with colinearity with magnetic anomaly trends, suggests that both surface water and pre-existing basement structures may play significant roles in con-trolling intraplate seismicity in the southern Great Lakes region.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".