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Record W7036498789

Caractérisation et surveillance d’un glissement rocheux actif d’une mine à ciel ouvert en utilisant le LiDAR

2020· other· fr· W7036498789 on OpenAlexaboutno aff

Bibliographic record

VenueCorpus Université Laval (Université Laval) · 2020
Typeother
Languagefr
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLidarTelmatologyDebris
DOInot available

Abstract

fetched live from OpenAlex

En Juillet 2012, une large rupture de pente s’est produite sur le mur Est de la mine LAB Chrysotile de Thetford Mines Québec, Canada. Cette rupture de pente a eu un impact irrémédiable sur la route régionale située au sommet de la pente, affectant l'économie des communes environnantes. L’objet de cet article est de comprendre ce glissement de terrain en utilisant à la fois le LiDAR à balayage laser terrestre (TLS) et aérien (ALS) . Depuis 2010, trois ALS et douze TLS ont été réalisés pour caractériser et surveiller le glissement. Le balayage laser a d'abord été utilisé pour étudier la géométrie du glissement : son volume, la topographie, la taille et l'orientation de l'escarpement, etc. Il a ensuite été utilisé pour étudier les déplacements 3D pour avoir une meilleure compréhension de la cinématique du glissement. Cet article montre clairement la capacité du balayage LiDAR à fournir des informations quantitatives pertinentes sur la masse rocheuse en mouvement.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.188
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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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