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Record W2336074103 · doi:10.1515/sggw-2015-0016

Concept of hybrid embankment

2015· article· en· W2336074103 on OpenAlexfundno aff
Masaharu Fukue, Zbigniew Lechowicz, Rie Takahashi, Kouji Uehara

Bibliographic record

VenueAnnals of Warsaw University of Life Sciences – SGGW Land Reclamation · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceConcordia University
KeywordsLeveeEnvironmentally friendlyNatural (archaeology)Geotechnical engineeringDiagenesisLand reclamationSoil stabilizationEngineeringCivil engineeringGeologyEnvironmental scienceSoil scienceEcologySoil waterGeochemistry

Abstract

fetched live from OpenAlex

Abstract An innovative technique which is similar to a natural process, i.e., biogeochemical (carbonate) diagenesis, is proposed to construct a hybrid embankment. In this study, the hybrid embankment is defined as a soil embankment which has a microbially induced framework structure of sand sheets and columns in the soft soil matrix. The sand materials are cemented with magnesium-calcite or dolomite, induced by ureolytic microbes. To design and construct hybrid embankments, fundamental problems, such as feasibility in terms of stability, geoenvironmental engineering practices, etc., are examined and discussed. It was shown that the hybrid embankment can be environmentally friendly and also can contribute solving technical and financial problems encountered in actual practice.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.061
GPT teacher head0.264
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2015
Admission routes1
Has abstractyes

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