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Record W4408440629 · doi:10.5194/egusphere-egu25-4981

Taiwan's mountain building and landscape evolution: A cosmogenic perspective

2025· preprint· en· W4408440629 on OpenAlexaff
Lionel Siamé, Romano Clementucci, Hao‐Tsu Chu, Chung‐Pai Chang, Jian-Cheng Lee, Laëtitia Léanni, Régis Braucher

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsASTER
Fundersnot available
KeywordsPerspective (graphical)GeographyEarth sciencePhysical geographyGeologyArchaeologyVisual artsArt

Abstract

fetched live from OpenAlex

Taiwan is a young arc-continent collisional orogen characterised by rapid exhumation, high relief, and a fluvial and landslide-dominated landscape. The obliquity between the convergence direction and the plate boundary trend creates gradients of uplift and variations in orogenic activity, with an immature orogen in the south, a mature orogen in the central and northern regions, and possible cessation of orogeny in the far north. Channel steepness strongly correlates with erosion rates, suggesting fluvial erosion as the dominant exhumation process, primarily driven by tectonic forcing. These processes maintain a quasi-equilibrium where erosion and uplift rates are nearly equal, shaping Taiwan’s dynamic and rapidly evolving landscape. Over the past two decades, in-situ produced cosmogenic nuclides, particularly 10Be in quartz-bearing rocks, have emerged as essential tools for studying bedrock erosion rates and landscape evolution. Early studies in Taiwan utilised atmospheric 10Be to measure sedimentation rates along continental margins, while later works employed in-situ 10Be to date glacial features, stream terraces, and soils, providing critical insights into surface deformation and climate. Applications of 10Be in modern river sediments revealed its capacity to address orogen-scale surface processes, with studies linking denudation rates to tectonic control in mature orogens. Recent research has refined these approaches, highlighting the effects of landslide sediment on 10Be concentrations and providing detailed spatial erosion patterns at the catchment scale. Building on this foundation, our presentation introduces a comprehensive dataset of unpublished spatial and temporal analyses, offering new perspectives on Taiwan’s topographic evolution. These data enhance our understanding of the interplay between surface processes and the construction of the central mountain range, enriching the broader narrative of Taiwan’s geomorphic evolution and the complexities of erosional processes driven by tectonics.

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 score0.396
Threshold uncertainty score0.992

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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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
Published2025
Admission routes1
Has abstractyes

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