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Record W2029007278 · doi:10.1139/e02-053

Three-dimensional velocity images beneath the KangDian Tethyan tectonic zone of China

2002· article· en· W2029007278 on OpenAlexaffvenue
Yike Liu, Xu Chang, Futian Liu, Ye Zheng

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
FundersChinese Academy of Sciences
KeywordsGeologyCrustTectonicsSeismologyTransition zoneDepth of focus (tectonics)Upper crustLow-velocity zoneMantle (geology)Oceanic crustPaleontologyLithosphereSubductionGeophysics

Abstract

fetched live from OpenAlex

Three-dimensional velocity images of the crust and upper mantle beneath the Kang–Dian Tethyan tectonic zone in China are constructed using P-wave travel-time residuals of earthquakes. The Kang–Dian Tethyan tectonic zone is a transitional zone in tectonic structures and an important topographic border line. It is also a zone of concentration of shallow-focus earthquakes. The imaging results indicate that there is a significant lateral heterogeneity in the crust and upper mantle beneath the Kang–Dian Tethyan tectonic zone in China. The velocity images of the upper crust show features closely related to the tectonic features on the surface. A low-velocity layer exists in a very wide range of the mid-crust. Almost all of the major earthquakes took place in the transition strips between high- and low-velocity zones in the crust above 20 km depth. From the velocity images at 20+0 and 50+0 km depth, respectively, we find that the epicenters of strong earthquakes with magnitude larger than 6.0 are almost entirely distributed in the low-velocity zones or on their boundaries.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.201
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2002
Admission routes2
Has abstractyes

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