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Record W1905433385 · doi:10.1139/cjce-2013-0069

Concrete pavement rehabilitation procedure using resonant rubblization technology and mechanical–empirical based overlay design

2013· article· en· W1905433385 on OpenAlexvenueno aff
Xin Qiu, Jianming Ling, Feng Wang

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsOverlaySubgradeSlabPavement engineeringAsphaltStructural engineeringCrackingEngineeringAsphalt pavementSieve (category theory)Geotechnical engineeringCivil engineeringComputer scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Reflective cracking distresses frequently occur on the hot mix asphalt (HMA) overlay due to the movements of the underlying Portland cement concrete (PCC). Rubblization was proven in North America to be an effective approach among slab fracturing technologies for solving the premature reflective cracking problem. This paper presents the procedure of applying the rubblization technology in HMA overlay design in a research effort in China to develop the Chinese standard. In the study, the validity of rubblization was analyzed by a trench survey and sieve tests; the layer moduli of the composite subgrade and rubblized concrete slab were determined using FWD and plate bearing tests and a conversion chart; the thickness design for the HMA overlay over the rubblized PCC pavement was conducted using a Chinese version mechanistic–empirical design process; and finally the in-service monitoring over the pavements built using the developed procedure was conducted to test the validity of the procedure.

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)0.000
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: none
Teacher disagreement score0.534
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations13
Published2013
Admission routes1
Has abstractyes

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