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Uplift History of the Eastern Pamir Inferred from Inversion of Thermochronometric Data and River Profile

2024· article· en· W4407836374 on OpenAlexaff
Yunpeng Wu, Rong Yang, Ruohong Jiao, Xiubin Lin, Hanlin Chen, Junfeng Gong, Xuhua Shi

Bibliographic record

VenueLithosphere · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGeologyInversion (geology)SeismologyTectonics

Abstract

fetched live from OpenAlex

Abstract The Pamir salient accommodates a great amount of Cenozoic India-Eurasia convergence in the forms of thrusting, strike-slip faulting, extension, and gneiss dome formation. It thus becomes a key location for exploring the orogenic tectonic evolution. Here, we focus on the Eastern Pamir where extensional deformation dominates during the late Cenozoic. We conducted low-temperature thermochronological dating on bedrock samples collected from the footwall of the Kongur Shan normal fault together with inversion of the longitudinal river profile of the Gez River. Our new zircon and apatite (U-Th)/He (ZHe and AHe) data reveal young ages in proximity to the normal fault and older ages adjacent to the western Tarim Basin. By inverting the Gez River profile together with published and new thermochronological ages, we obtained a sustained uplift rate of ~3 mm/yr in the Kongur Shan dome since ~8 Ma, contrasting with no significant uplift to the east of the dome before the Pliocene. This uplift pattern can be interpreted as a result of the upward extrusion of crust materials along a flat–ramp–flat thrust fault at depth under the context of convergence.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 head0.039
GPT teacher head0.203
Teacher spread0.164 · 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 designSimulation or modeling
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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