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Record W6999157056

Characterization and monitoring of the Åknes landslide using terrestrial laser scanning

2008· article· en· W6999157056 on OpenAlexfundno aff

Bibliographic record

VenueSERVAL (Université de Lausanne) · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersUniversité de LausanneQueen's University
KeywordsFusible alloyTubulopathyNucleofectionTSG101ProteogenomicsDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

Terrestrial laser scanning (TLS) provides high-resolution point clouds of the topography and new TLS instruments with ranges exceeding 300 m or even 1000 m are powerful tools for characterizing and monitoring slope movements. This study focuses on the 35 million m3 Åknes rockslide in Western Norway, which is one of the most investigated and monitored rockslides in the world. The TLS point clouds are used for the structural analysis of the steep, inaccessible main scarp of the rockslide, including an assessment of the discontinuity sets and fold axes. TLS acquisitions in 2006, 2007 and 2008 provide information on 3-D displacements for the entire scanned area and are not restricted like conventional survey instruments to single measurement points. The affine transformation matrix between two TLS acquisitions precisely describes the rockslide displacements and enables their separation into translational components, such as the displacement velocity and direction, and rotational components, like toppling. This study shows the ability of TLS to obtain reliable 3-D displacement information over a large, unstable area. Finally, a possible instability model for the upper part of Åknes rockslide explains the measured translational and rotational displacements by a combination of southward planar sliding along the gneiss foliation, gravitational vertical settlement along the complex, stepped basal sliding surface and northward toppling toward the opened graben structure.

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 score0.103
Threshold uncertainty score0.249

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 head0.014
GPT teacher head0.190
Teacher spread0.177 · 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
Published2008
Admission routes1
Has abstractyes

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