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Record W2001652893 · doi:10.1139/t08-121

25 years of movement monitoring on South Peak, Turtle Mountain: understanding the hazard

2009· article· en· W2001652893 on OpenAlexafffundvenueabout
Corey Froese, Francisco Moreno, Michel Jaboyedoff, D. M. Crudën

Bibliographic record

VenueCanadian Geotechnical Journal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsAlberta EnergyUniversity of AlbertaGeological Survey of Canada
FundersUniversity of Calgary
KeywordsGeologyDeformation monitoringElevation (ballistics)Margin (machine learning)SeismologyPhysical geographyCartographyGeographyDeformation (meteorology)EngineeringOceanography

Abstract

fetched live from OpenAlex

In 1981, an Alberta Government project upgraded the monitoring of South Peak, Turtle Mountain, on the south margin of the 1903 Frank Slide. The monitoring program aimed at understanding the rates of deformation over large, deep fractures encompassing South Peak and predicting a second large rock avalanche on the mountain. The monitoring program consisted of a complement of static ground points and remotely monitored targets measured periodically, and climatic, microseismic, and deformation data collected automatically on daily intervals and archived. In the late 1980s, developmental funding for the monitoring program ceased and some of the installations fell into disrepair. Between May 2004 and September 2006, readings from the remaining functional monitoring points were compiled and interpreted. In addition, readings compiled previously were re-interpreted based on a more recent understanding of short-term movement patterns and climatic influences. These observations were compared with recent observations from an airborne light detection and ranging (LiDAR) digital elevation model and field photographs to give more precise estimates of the overall rates, extent, and patterns of motion for the past 25 years.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.440

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 integrity0.0000.001
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 head0.018
GPT teacher head0.222
Teacher spread0.204 · 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

Citations49
Published2009
Admission routes4
Has abstractyes

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