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Record W2022793647 · doi:10.1111/1755-6724.12397

Lithospheric Electrical Structure across the Eastern Segment of the Altyn Tagh Fault on the Northern Margin of the Tibetan Plateau

2015· article· en· W2022793647 on OpenAlexaff
Gaofeng Ye, Sheng Jin, Martyn Unsworth, JONES Alan G, Hao Dong

Bibliographic record

VenueActa Geologica Sinica - English Edition · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyMagnetotelluricsSeismologyLithosphereInversion (geology)CrustRiftThrustFault (geology)Strike-slip tectonicsThrust faultPlateau (mathematics)TectonicsPaleontology

Abstract

fetched live from OpenAlex

Abstract Project INDEPTH (InterNational DEep Profiling of Tibet and the Himalaya) is an interdisciplinary program designed to develop a better understanding of deep structures and mechanics of the Tibetan Plateau. As a component of magnetotelluric (MT) work in the 4th phase of the project, MT data were collected along a profile that crosses the eastern segment of the Altyn Tagh fault on the northern margin of the plateau. Time series data processing used robust algorithms to give high quality responses. Dimensionality analysis showed that 2D approach is only valid for the northern section of the profile. Consequently, 2D inversions were only conducted for the northern section, and 3D inversions were conducted on MT data from the whole profile. From the 2D inversion model, the eastern segment of the Altyn Tagh fault only appears as a crustal structure, which suggests accommodation of strike slip motion along the Altyn Tagh fault by thrusting within the Qilian block. A large‐scale off‐profile conductor within the mid‐lower crust of the Qilian block was revealed from the 3D inversion model, which is probably correlated with the North Qaidam thrust belt. Furthermore, the unconnected conductors from the 3D inversion model indicate that deformations in the study area are generally localized.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.298
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.236
Teacher spread0.216 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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