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Record W2003553243 · doi:10.1139/t10-075

Undrained shear strength properties of organic harbor mud at low consolidation stress levels

2011· article· en· W2003553243 on OpenAlexvenueno aff
Benjamin Friedrich Schlue, Tobias Mörz, Stefan Kreiter

Bibliographic record

VenueCanadian Geotechnical Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersTechnische Universität BerlinDeutsche ForschungsgemeinschaftBrown University
KeywordsOedometer testConsolidation (business)DredgingGeotechnical engineeringShear strength (soil)GeologyShear (geology)Direct shear testSoil water

Abstract

fetched live from OpenAlex

Dredging operations in European harbors for maintenance of navigable water depth produce vast amounts of harbor mud. Between 2005 and 2007, the second largest harbor construction project in Germany was designed as a pilot study, using dredged harbor mud as backfill material to avoid expensive deposition or ex situ treatment. During this project, strong surface deformations of the backfill highlighted the need for an improved assessment of undrained shear strength of naturally liquid harbor mud. The strength of harbor mud cannot be measured accurately under corresponding low in situ effective stress levels by standard laboratory tests. Therefore, a large-scale oedometer cell with a diameter of 22 cm was designed, providing the opportunity to perform vane shear measurements during consolidation. This study shows that East Harbor mud is a very sensitive, organogenic clay of extremely high plasticity, exhibiting very small undrained shear strength when compared with other cohesive soils. Both the peak and residual undrained shear strengths are shown to increase about 3%–4% per log-cycle increase in secondary compression time (days).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.179
Teacher spread0.158 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2011
Admission routes1
Has abstractyes

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