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Record W2018699102 · doi:10.1139/t00-003

Hydraulic conductivity of kaolinite-silt mixtures subjected to closed-system freezing and thaw consolidation

2000· article· en· W2018699102 on OpenAlexvenueno aff
Jean‐Marie Konrad, Martin Samson

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic conductivitySiltKaoliniteConsolidation (business)Geotechnical engineeringVoid ratioCompressibilityPermeability (electromagnetism)Materials scienceGeologySoil scienceMineralogySoil waterThermodynamicsChemistry

Abstract

fetched live from OpenAlex

Kaolinite-silt mixtures at different clay contents were subjected to closed-system freezing and thaw consolidation to obtain data on the hydraulic conductivity of thawed samples. A simplified void ratio model was developed based on the compressibility characteristics of the clay aggregates and the freezing-induced suctions. The close agreement between predictions and observations suggests that the assumptions of the model are reasonable, especially that maximum freezing-induced suctions developed in the clay aggregates are related to the temperature at which no significant change in unfrozen water content occurs rather than the actual freezing temperature. Furthermore, the compression characteristics of thawed mixtures is essentially controlled by the recompression of the clay aggregates in the overconsolidated domain. The void ratio model is linked to a permeability model that suggests that the hydraulic conductivity of thawed mixtures can be defined by a reference value of the unfrozen soil and a parameter specific to each mixture.Key words: freeze-thaw, laboratory, hydraulic conductivity, conceptual model, silt, kaolin.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.995

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)0.0060.000

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 head0.027
GPT teacher head0.230
Teacher spread0.203 · 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 designObservational
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

Citations89
Published2000
Admission routes1
Has abstractyes

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