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Record W2334451404 · doi:10.1061/40971(310)66

Comparison of Geotextile and Geogrid Reinforcement on Unpaved Road

2008· article· en· W2334451404 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeoCongress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsGeotextileGeogridSubgradeGeosyntheticsGeotechnical engineeringReinforcementDrainageAggregate (composite)EngineeringMaterials scienceStructural engineeringComposite material

Abstract

fetched live from OpenAlex

Geosynthetics, such as geotextile and geogrid, are commonly used for the reinforcement of unpaved roads. The geosynthetics can reduce the thickness of aggregate required above soft subgrade and improve the durability of the unpaved road. Both geotextile and geogrid perform similar functions and often equivalently. However, the similar functions come from different reinforcement mechanisms. The reinforcement by geogrid mainly results from lateral constraint provided by interlocking between aggregate and geogrid. In contrast, geotextile functions through a number of ways, including reinforcement through interaction friction, separation between subgrade soil and base course material, filtration, and drainage. Several methods are available to design unpaved road using these two reinforcements. The focus of this paper is to review and discuss the reinforcement mechanisms from geotextile and geogrid, as well as methods used for the design of unpaved roads with the two reinforcements.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.548

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)0.0000.000

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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