NLL-SSST-coherence high-precision earthquake location catalog for the M 7.0, 2025 Alaska-Yukon Hubbard Glacier earthquake sequence
Bibliographic record
Abstract
Hypocenter catalog files and visualization of high-precision, NLL-SSST-coherence earthquake locations for the M 7.0, 2025 Alaska-Yukon Hubbard Glacier earthquake sequence and background seismicity (2020-01-01 to 2025-12-13). NLL-SSST-coherence (Lomax and Savvaidis, 2022; Lomax and Henry, 2023; Lomax et al., 2024) is an enhanced, absolute-timing earthquake location procedure which 1) iteratively generates spatially varying travel-time corrections to improve multi-scale location precision and 2) uses waveform similarity to improve fine-scale location precision. Relocations performed with phase arrival data available from https://earthquake.usgs.gov/earthquakes Initial seismic velocity model is the scak model used by the Alaska Earthquake Center, from:Silwal, V., & Tape, C. (2016). Seismic moment tensors and estimated uncertainties in southern Alaska. Journal of Geophysical Research: Solid Earth, 121(4), 2772–2797. https://doi.org/10.1002/2015JB012588 Visualizations include surface fault traces from https://www.usgs.gov/programs/earthquake-hazards/faults This repository contains: Selected Visualization imagesplotted epicenters are from expectation hypocenters (expect_lat, expect_lon in csv file)only events with location error (68% confidence EllipsoidLen3) ≤ 10 km are plotted Full catalog in CSV format:CSV file data columns correspond to selected fields of the of NonLinLoc Hypocenter format output http://alomax.free.fr/nlloc/soft7.00/formats.html#_location_hypphs_ CSV format description:FIELD : DESCRIPTION date-time : maximum likelihood* hypocenter origin time latitude : maximum likelihood* hypocenter latitude (deg) longitude : maximum likelihood* hypocenter longitude (deg) depth : maximum likelihood* hypocenter depth (km below reference level (e.g. sea-level)) RMS : root-mean-square of phase residuals at hypocenter (sec) Nphs : number of readings used for location Gap : maximum azimuth gap between stations used for location (deg) Dist : distance of closest station to maximum likelihood* hypocenter (Non-GLOBAL: km, GLOBAL: deg) errH : horizontal error (semi-major axis of 68% confidence error ellipse) (km) errZ : depth error (68% confidence: sqrt(2.30 * covariance(zz))) (km) Mamp : amplitude (i.e. ML) magnitude Mdur : duration magnitude expect_lat : expectation hypocenter latitude (deg) expect_lon : expectation hypocenter longitude (deg) expect_z : expectation hypocenter depth (km below reference level (e.g. sea-level)) EllipsoidAz1 : azimuth of semi-minor-axis of 68% confidence ellipsoid (deg) EllipsoidDip1 : dip of semi-minor-axis of 68% confidence ellipsoid (deg) EllipsoidLen1 : length of semi-minor-axis of 68% confidence ellipsoid (km) EllipsoidAz2 : azimuth of semi-intermediate-axis of 68% confidence ellipsoid EllipsoidDip2 : dip of semi-intermediate-axis of 68% confidence ellipsoid (deg) EllipsoidLen2 : length of semi-intermediate-axis of 68% confidence ellipsoid (km) EllipsoidLen3 : length of semi-major-axis of 68% confidence ellipsoid (km) minHorUnc : semi-minor axis of 68% confidence ellipse (km) maxHorUnc : semi-major axis of 68% confidence ellipse (km) azMaxHorUnc : azimuth of major axis of 68% confidence ellipse (deg) pdfVolume : integral over octree cells of volume * cell probability (if octree search used) mech_strike : strike of double couple mechanism (deg) mech_dip : dip of double couple mechanism (deg) mech_rake : rake of double couple mechanism (deg) mech_misfit : misfit of mechanism determination mech_Nobs : number of first motion observations used in mechanism determination publicId : event id string * expectation hypocenter if LOCHYPOUT SAVE_NLLOC_EXPECTATION used
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.154 | 0.067 |
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".