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Record W3207323399 · doi:10.1139/cgj-2020-0696

Effects of in situ wetting–drying cycles on the mechanical behaviour of an intact loess

2021· article· en· W3207323399 on OpenAlexvenueno aff
Qingyi Mu, Haiqing Dong, Hongjian Liao, Chao Zhou, S.B. Li, J. W. Zhang

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsLoessWettingGeotechnical engineeringMaterials scienceIn situSuctionSiltGeologySwellingComposite materialChemistryGeomorphology

Abstract

fetched live from OpenAlex

In situ wetting–drying cycles significantly and repeatedly influence the soil water content in the active zone but not in the steady zone. To investigate effects of in situ wetting–drying cycles on the mechanical behaviour of intact loess, a series of pressure plate tests was carried out with an intact loess sampled from the active and steady zones. Results show that the specimens from the steady zone have higher yield stresses at given suctions and a larger inclination of normalized loading collapse (LC) curve than the specimens from the active zone. As evidenced by the scanning electron microscopy results, the clay particles accumulating around the contacts between silt particles are widely observed in the former specimens but not in the latter specimens. The distribution of clay particles in the former specimens results in a stabilized skeleton with mechanical properties sensitive to suction variations. On the other hand, the maximum collapse potential of the specimen from the steady zone is 37% larger than that of the specimen from the active zone, mainly because of the larger inclination of normalized LC curve owned by the former specimen.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.451

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 integrity0.0000.001
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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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

Citations35
Published2021
Admission routes1
Has abstractyes

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