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Record W3090889054 · doi:10.1051/geotech/2020016

Évaluation quantitative du risque rocheux : de la formalisation à l’application sur les zones urbanisées ou urbanisables

2020· article· fr· W3090889054 on OpenAlexaff
Manon Farvacque, Nicolas Eckert, Franck Bourrier, Christophe Corona, Jérôme Lopez‐Saez, David Toe

Bibliographic record

VenueRevue Française de Géotechnique · 2020
Typearticle
Languagefr
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsImpact
FundersAgence Nationale de la Recherche
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Les chutes de blocs représentent un aléa majeur dans les zones montagneuses, menaçant infrastructures collectives, zones urbanisées et vies humaines. Les conséquences de ces événements peuvent être importantes pour les collectivités locales ainsi que les pouvoirs publics, qui restent démunis en matière de méthode de diagnostic et d’analyse du risque. Dans ce contexte, l’évaluation du risque rocheux par une approche de type QRA ( quantitative risk assessment ) est devenue incontournable pour l’aménagement des territoires de montagne et le choix des stratégies destinées à réduire le risque. Cependant, en pratique, la QRA reste peu utilisée et développée. À cet égard, cet article propose de renforcer les bases formelles du calcul du risque dans le domaine des chutes de blocs et démontre sa faisabilité sur des zones urbanisées/urbanisables. Les effets de la non-stationnarité du phénomène, et l’apport de nouvelles mesures de risque permettant les arbitrages court terme/long terme, sont également abordés. Le potentiel de l’approche est illustré par le cas d’étude réel de la commune de Crolles, dans les Alpes françaises.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations3
Published2020
Admission routes1
Has abstractyes

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