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Record W2261880445 · doi:10.1139/cgj-2015-0295

Laboratory test study on the effect of freeze–thaw cycles on strength and hydraulic conductivity of high water content stabilized dredged sediments

2016· article· en· W2261880445 on OpenAlexvenueno aff
Gregory Paul Makusa, Josef Mácsik, Göran Holm, Sven Knutsson

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersLuleå Tekniska Universitet
KeywordsHydraulic conductivityCyclingCompressive strengthConsolidation (business)Geotechnical engineeringMaterials scienceComposite materialGeologySoil scienceSoil water

Abstract

fetched live from OpenAlex

Dredged sediments with initial water contents between 200% and 400% were treated with single and composite binders. Samples were subjected to open and semi-closed freeze–thaw (f–t) cycles to investigate the impact of f–t cycling on hydraulic conductivity (HC) and unconfined compressive strength (UCS). A grace period (GP) for thaw consolidation is included to assess healing potential of the affected stabilized mass. Findings of this study show that the impact of f–t cycles depends on initially achieved UCS and HC values prior to the f–t cycling and time of testing after f–t cycles. The HC of specimens with an initial UCS value of 87 kPa increased with number of f–t cycles. The UCS values decreased in the range of 50%–80% when specimens were tested directly after the thaw period and values decreased in the range of 14%–60% when specimens were tested at the end of the GP. The HC of specimens with an initial UCS value of 299 kPa remained almost the same. These samples experienced permanent loss in the UCS values, irrespective of time of testing. Detrimental effects of the freezing action on the UCS were greater under semi-closed than open freezing conditions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.993

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 studies0.0000.001
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 head0.015
GPT teacher head0.218
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2016
Admission routes1
Has abstractyes

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