Cluster analysis can identify differences in earthquake swarm patterns along the Mid-Atlantic Ridge
Bibliographic record
Abstract
The Mid-Atlantic Ridge (MAR) is the longest divergent plate boundary in the world, with evident seafloor spreading, transform faults, and hydrothermal vents generating earthquake swarms as tectonic plates move apart. Earthquake swarms are generally defined as a sequence lacking a mainshock event (e.g., a number of similar magnitude events occurring close in space and time). Previous work on swarms on the Mid-Atlantic Ridge have focussed on specific events, where recording equipment generate a local view of an earthquake swarm. Although these studies provide high-resolution information into an event, the work is limited in space (local area) and time (days or months). As a result, there is currently no up-to-date large-scale analysis across the length of the ridge which would provide regional information on Wilson Cycle processes of rifting. Here, we apply a clustering algorithm to an earthquake database across the MAR to identify spatially and temporally correlated swarms to establish a regional analysis of earthquake swarms on the Mid-Atlantic Ridge. For our study, we use the available United States Geological Survey (USGS) earthquake database to analyse earthquake events across four different sections of the MAR (Reykjanes Ridge, Northern, Central, and Southern MAR) over the past 25 years (7,000+ earthquakes in total). Within this database, we find over 800 swarm events (compared to around 150 swarms in the past 50 years of published literature). We explore the spatial and temporal links between earthquakes and establish some similarities throughout the ridge. Specifically, swarm events are short lived, often starting and finishing within a day. Furthermore, the earthquakes within a swarm are mainly between 10-20 km of each other. An advantage of this large-scale approach to identifying swarms through cluster analysis is that we can begin to establish swarm characteristics and provide quantifications on spatial and temporal values.Notably, we have identified 600+ swarms not discussed in the current literature with our work providing a standardised output for comparing swarms across the whole ridge. We highlight that MAR is not a homogenous entity, with Reykjanes Ridge behaving fundamentally different to the rest of the ridge. The large-scale analysis from our work here provides future studies with a benchmark to exploring spatial and temporal changes on this significant Wilson Cycle feature on our planet.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".