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Record W4405357824 · doi:10.1002/9781394195947.ch5

Geodetic Observations of Tectonic Deformation in Alaska and Western Canada: The EarthScope Revolution

2024· other· en· W4405357824 on OpenAlexaboutno aff
Julie Elliott, Jeffrey T. Freymueller, Ronni Grapenthin

Bibliographic record

VenueGeophysical monograph · 2024
Typeother
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
FundersU.S. Geological SurveyNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsGeodetic datumGeologyTectonicsSeismologyGeodesyDeformation (meteorology)Oceanography

Abstract

fetched live from OpenAlex

The number of GPS sites in Alaska and western Canada has exploded over the past 15 years, largely due to the PBO/NOTA stations installed as part of the NSF-funded EarthScope project. This expanded geodetic data set has provided an unprecedented view of deformation along the north Pacific margin. The entire region moves in ways distinct from stable North America. Long-term motion of the upper plate includes northwestward motion in southeast Alaska and the St. Elias region, a clockwise rotation from the southeast Alaska coast into the Northern Cordillera of Canada, a series of counterclockwise rotations south of the Denali Fault, and southerly motion in northern Alaska. Geodetically determined coupling along the subduction interface varies greatly, with correlations between past earthquakes, areas of high and moderate coupling, and lateral coupling boundaries. GPS data from a number of large earthquakes have captured complex slip patterns, evolution of slip during events, and interactions between earthquakes. Postseismic deformation from several large earthquakes, including the 1964 M9.2 Great Alaska and the 2002 M7.9 Denali earthquakes, is ongoing. Transient slow slip events along the subduction interface may accommodate part or most of the slip budget in areas of partial coupling.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.196
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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