A New Year’s Day icebreaker: icequakes on lakes in Alberta, Canada
Bibliographic record
Abstract
Any process that causes a sudden brittle failure of material has the potential to cause earthquake-like seismic events. Cryoseisms represent an underreported class of seismic event due to their (often) small magnitudes. In this paper, we document the phenomenon of some of the largest magnitude lake-associated icequakes (ML 2.0) yet reported. These events occurred nearly simultaneously (within ∼2 h) on geographically separate lakes in Alberta, Canada, starting 1 January 2018. We conjecture that these events were caused by the sudden brittle failure of lake ice due to thermal expansion; the effects of the thermal expansion were compounded by the lack of insulating snow cover, high lake water levels, and a rapid onset of atmospheric warming. These factors also contributed to ice-jacking — a repeating process in which thermal contraction produces tensile cracks (leads) in lake ice that are then filled with water that is frozen during the cooling cycle. Thus, any subsequent thermal expansion must be accommodated by new deformation or brittle failure. This ice-jacking process caused creeping ground deformation after the initial brittle failure and again two weeks later following a second warming period. In many cases, the resulting ground deformation was significant enough to cause property damage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".