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Research on the Delimitation Criterion of Long Sustained Slope Sections Based on Permanent Deformation of Asphalt Pavement

2013· article· en· W2072586607 on OpenAlexaff
Er Hu Yan, Fei Chen, Fu Pu Li, Zhijun Wang

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldEngineering
TopicCivil and Geotechnical Engineering Research
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsTruckRutDeformation (meteorology)AsphaltGeotechnical engineeringAsphalt pavementStructural engineeringPoint (geometry)EngineeringGeologyEnvironmental scienceMaterials scienceMathematicsAutomotive engineeringGeometryComposite material

Abstract

fetched live from OpenAlex

The permanent deformation is the key failure of asphalt pavements, especially for long sustained slope sections, and it is necessary to research the delimitation criterion of long sustained slope sections. Firstly, the disease survey of long sustained slope sections is carried out, the change of truck speed and load are described and its impaction on rutting failure is analyzed. Finally, continuous speed of heavy truck is point out to be used as the delimitation criterion, based on a new model of continuous speed of heavy truck which developed and optimized according to permanent deformation.

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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.049
GPT teacher head0.345
Teacher spread0.296 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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