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Record W3192255389 · doi:10.1007/s11069-021-04954-9

Rockfall susceptibility and runout in the Valley of the Kings

2021· article· en· W3192255389 on OpenAlexaff
Lukovic Marija, Martin Ziegler, Jordan Aaron, Matthew A. Perras

Bibliographic record

VenueNatural Hazards · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsYork University
FundersEidgenössische Technische Hochschule Zürich
KeywordsRockfallCliffGeologyDebrisRock mass classificationExcavationLandslideNatural hazardArchaeologyGeomorphologyMining engineeringGeographyPaleontologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The UNESCO world heritage site Valley of the Kings or Wadi el-Moluk (وادي الملوك) near Luxor, Egypt, hosts unique burial places of Egyptian kings and royals from the New Kingdom (c. 1539–1075 BCE) and attracts about 0.5 to 2 million tourists per year. Very steep to subvertical cliffs of Thebes Limestone surround the Valley of the Kings. The rock mass is cut by frequent joints and faults making the cliff walls prone to rockfalls. However, only few rockfall debris are found in the valley, likely due to natural remobilisation by flood events and artificial clearings and excavation works that rendered the natural debris cover over the millennia. This work focuses on rockfall susceptibility and runout and makes use of new high-resolution landscape surface models utilising terrestrial laser scanning. We investigated rockfall release areas by exploring rock mass fractures at 23 cliff segments and analysed the kinematics of potential rockfalls. Furthermore, we estimated potential rockfall deposition areas with CONEFALL supported by nine numerical simulations of single rockfall events using Rockyfor3D. We found that nearly 4500 m 2 (26%) of the public walking paths and 24 out of 64 tomb entrance areas locate within potential rockfall runout zones.

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 score0.088
Threshold uncertainty score0.315

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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