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Record W4413023671 · doi:10.1038/s41467-025-62493-4

Preconditioning of sediment failure by astronomically paced weak-layer deposition

2025· article· en· W4413023671 on OpenAlexaff
Xingxing Wang, Vittorio Maselli, Luca Flessati, Hongbin Wang, Zhilei Sun, Qing Wang, Jie Chen, Qing Li, Stefano Alberti, Markus Kienast, Shucheng Xie, Qiliang Sun

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsDalhousie University
FundersChina Geological SurveyNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsDeposition (geology)Layer (electronics)SedimentGeologyHydrology (agriculture)Computer scienceMaterials scienceGeomorphologyGeotechnical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Low-strength sediment layers within continental slope strata precondition submarine sediment for failure, potentially leading to destructive tsunamis. Using geophysical and Ocean Drilling Program well data, here we show that the glide planes of widespread submarine failures in the northern South China Sea, dated to the glacial stages following the Mid-Pleistocene Transition, have higher opal content, particle size, and porosity, which reduce the undrained shear strength. Cyclic weak-layer deposition, modulated at Milankovitch time scale, was controlled by increased ocean primary productivity and sedimentation rates linked to high-amplitude sea-level fluctuations and intensified winter monsoons. This study represents an important step forward for understanding how climate influences the formation of weak layers and the stability of continental slope globally.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.242
Teacher spread0.234 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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