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Record W4283802526 · doi:10.1680/jgele.22.00036

Influence of fines content on the undrained flow instability of loess

2022· article· en· W4283802526 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGéotechnique Letters · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLoessInstabilityGeotechnical engineeringVoid (composites)Materials scienceVoid ratioMonotonic functionPlasticityFlow (mathematics)Stress pathGeologyMechanicsGrain sizeComposite materialMathematicsPhysicsGeomorphology

Abstract

fetched live from OpenAlex

The influence of fines content (FC) on flow instability of intact and reconstituted Chinese loess is studied under undrained monotonic loading using conventional triaxial tests. The undrained behaviour of a mixed loess system indicates that the increasing plastic fines reduce the peak strength with little effect on the critical state friction angle. The changing FC can result in parallel translation and rotation of the critical state lines (CSLs) of reconstituted loess in the volumetric plane. A coarse-grain- to fine-grain-dominant transition is found as FC attains 55·5%, with a convergence of CSL for FC ranging from 55·5 to 87·9% using the equivalent interfine void ratio. A similar trend is found for intact specimens, suggesting that fines may act as void fillers at low-stress levels, which indicates a competing effect of structure and interfine contacts. The modified state parameter is robust in characterising the flow behaviour of the Chinese loess with revised range and corresponding descriptors.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.558

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)0.0010.000

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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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