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Record W4282969888 · doi:10.1002/ppp.2151

Development of a rapid active layer detachment slide in the Fenghuoshan Mountains, Qinghai–Tibet Plateau

2022· article· en· W4282969888 on OpenAlexaff
Guanli Jiang, Siru Gao, Antoni G. Lewkowicz, Hongting Zhao, Shouji Pang, Qingbai Wu

Bibliographic record

VenuePermafrost and Periglacial Processes · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of OttawaEnvironment and Climate Change Canada
FundersNational Natural Science Foundation of China
KeywordsPermafrostGeologyPlateau (mathematics)Elevation (ballistics)Active layerGeomorphologyPhysical geographyLayer (electronics)Oceanography

Abstract

fetched live from OpenAlex

Abstract An active layer detachment slide (ALDS) in the interior portion of the Qinghai–Tibet Plateau (QTP) was investigated within 2 days of its formation on September 21, 2018. The ALDS developed on a relatively gentle slope (4.8° to 9°) at an elevation of 4,850 m above sea level (asl) and was about 145 m long and 45 m wide, with a headscarp 2.2–2.5 m high. Analyses of meteorological data and soil temperatures indicated that it was probably triggered by a record thaw depth which intersected a layer with high ice content at the base of the active layer and in the top of the permafrost. Based on the time window, the minimum downslope velocity of the main slide mass was about 20 m/h which is higher than previously reported values. The ALDS ran into the embankment of the Qinghai–Tibet Railway (QTR) but did not damage the railbed. However, extensive rehabilitation of the slope was needed subsequent to the failure to clear the slide mass and as minor headscarp recession and thaw settlement continued on the slope. In this work, we describe this feature and the most likely mechanisms of development.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.041
GPT teacher head0.260
Teacher spread0.219 · 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.

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

Citations29
Published2022
Admission routes1
Has abstractyes

Explore more

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