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Record W4405099385 · doi:10.22215/etd/2024-16281

Influence of Initial State on Runout in Flume Experiments on Remoulded Leda Clay

2024· dissertation· en· W4405099385 on OpenAlexaff
Louai Anwar Alshafti

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsFlumeTailingsGeotechnical engineeringGeologyResidual strengthSlope failureResidualSlope stabilityMaterials scienceFlow (mathematics)Composite materialMechanics

Abstract

fetched live from OpenAlex

Flowability" of tailings refers to their potential to loose substantial strength in the event of some failure, in the context of a potential flow of tailings of a substantial distance and associated consequences.Tailings which are flowable may travel a distance with associated severe consequences, while those that are not flowable will not, despite potentially still losing some strength during failure.While flowability in hard rock tailings is connected to liquefaction, for clayey tailings it is linked to the sensitivity and residual strength.The work presented in this thesis, part of the large project on flowability of clayey tailings, studies induced failure of high water content remoulded Leda clay (Champlain Sea Clay), as a reusable geomaterial sufficiently similar to some clayey tailings, to use in initial experiments simulating failure and runout.A large database of flume tests, with a range of residual and peak strengths are generated.The failure and runout from these tests are analyzed using different analytical methods.The comparison of the experiments with the analytical methods show that both residual and peak strength affect the runout, but more sophisticated analyses should be used in future to understand the failure and runout mechanisms.II

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.913

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 head0.016
GPT teacher head0.289
Teacher spread0.273 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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