MétaCan
Menu
Back to cohort
Record W2062770843 · doi:10.1139/l03-018

Prévision par modélisation numérique de la zone de risque bordant un tronçon de rivière subissant une crue exceptionnelle

2003· article· en· W2062770843 on OpenAlexvenueaboutno aff
Tew‐Fik Mahdi, Claude Marché

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsFlooding (psychology)TributaryGeologyLandslideHydrology (agriculture)Flood mythHydraulicsGeotechnical engineeringErosionGeomorphologyEngineeringCartographyGeography

Abstract

fetched live from OpenAlex

The direct impacts of floods are often considered as limited to the maximum downstream area exposed to the flooding. Considering the size of exceptional floods, the river bed could undergo deep changes. Pairing the GSTARS sediment transport model to a slope stability model (modified Bishop method) that we developed, this paper presents a methodology leading to the definition of a true safety zone along the shores as it takes into account the risk of floods and soil movements: each section of this river undergoes changes due to sediment-fluvial hydraulics ( erosion-deposit) and then eventual landslides modify the profiles. To analyze this, we had first to determine the hydraulic and geotechnical characteristics then use them to test the slope stability of the various legs of the watercourse before and during flooding. The application of this method to a tributary of the Saguenay River for the 1996 "downpour" shows a very good correlation of results with those collected in situ. The method can be directly applied to define the anticipated evacuation zone in case of dam failure.Key words: flooding, evacuation zone, numerical simulations, slope stability, transportation of solids.[Journal Translation]

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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 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

Citations15
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207