Bibliographic record
Abstract
Hundreds of thousands of earthquakes were reported in Alaska in the decade between 2013 and 2022. They span a wide range of tectonic sources, ranging in magnitude up to 8.2 and in depth down to 300 km. The Alaska–Aleutian subduction zone remained the main source of the largest earthquakes, claiming eight out of nine magnitude 7+ events. The remaining single earthquake over magnitude 7 occurred along the transform plate boundary in southeast Alaska. Northern regions of Alaska produced a number of energetic earthquake swarms that lasted from weeks to years. Observations of significant earthquakes and swarms greatly benefited from the EarthScope USArray project that blanketed Alaska and western Canada with a regular grid of new seismic sites starting in the mid-2010s. This chapter presents a review of published research on rupture processes of significant earthquakes constrained using seismic, geodetic, and remote sensing data, as well as new data and analyses of the aftershock sequences as recorded by regional stations. It focuses on descriptions of magnitude 7+ earthquakes in the Aleutian Islands, magnitude 6+ earthquakes in southern and southeast Alaska, magnitude 5+ events in the western and interior regions, and earthquakes as low as magnitude 4 in the northeastern Brooks Range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".