Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south‐central Alaska
Bibliographic record
Abstract
Abstract Seismic hazards in subduction settings typically arise from megathrust, intraslab and crustal earthquake sources. Despite the frequent occurrence of intraslab earthquakes in subduction zones and their potential threat to communities, their long‐term recurrence behaviour is barely studied. Sedimentary sequences in lakes may register ground shaking from different seismic sources. This study investigates two long sediment cores (13 m and 16 m) from Skilak Lake, a proglacial lake in south‐central Alaska, to evaluate whether different seismic sources leave a distinct imprint. The sedimentary record shows a continuously varved sediment sequence, occasionally interrupted by turbidites, slump deposits and tephra beds. Turbidites and slump deposits were objectively identified using a statistical outlier analysis on varve thickness. The earthquake origin of these deposits was ascertained by resemblance with deposits induced by instrumentally recorded earthquakes (for example, 1964 ce Mw 9.2 megathrust and 1954 ce Mw 6.4 intraslab earthquakes) and correlation with multiple coeval landslide deposits on sub‐bottom profiles. The Skilak Lake record chronicles 19 earthquakes with moderate to very high confidence level in the past 1350 years. The sedimentary evidence of instrumentally‐recorded intraslab and megathrust earthquakes within the past 70 years demonstrates that not only megathrust earthquakes, but also past intraslab events are recorded. Although reported seismic intensities at Skilak Lake are comparable for the 1964 ce megathrust and the 1954 ce intraslab earthquakes, the long duration and low frequency content of seismic ground motion during megathrust earthquakes facilitate the triggering of multiple, voluminous landslides and the generation of megaturbidites. In contrast, the shorter duration and higher frequency source spectrum of intraslab earthquakes may only induce surficial slope remobilization and the generation of thinner turbidites. This study demonstrates that the sedimentary record of Skilak Lake has the potential to decipher multiple seismic sources, which opens possibilities for a comprehensive seismic hazard analysis for south‐central Alaska.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".