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Record W1984180338 · doi:10.5539/jsd.v2n3p102

Research on the Parameters of Environment-Friendly Recycled Road Materials

2009· article· en· W1984180338 on OpenAlexvenueno aff
Yuan-Chen Guo, Kewei Sun

Bibliographic record

VenueJournal of Sustainable Development · 2009
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
FundersNational Development and Reform Commission
KeywordsCementAggregate (composite)Compressive strengthMaterials scienceBuilding materialEnvironmentally friendlyEnvironmental scienceComposite material

Abstract

fetched live from OpenAlex

The feasibility of propagating road materials in the use of contracture wastes especially contented great amount waste bricks were researched in three aspects: Performance of recycled aggregate, mechanical properties of renewable road materials, compression - splitting indexes. Conclusions are as following: recycled aggregates contenting great amount waste bricks in place of natural aggregates are feasible from the point of view on technical and technological. The performances of recycled aggregates have a significant impact on properties of renewable road material. Whether it is cement stabilized RCA material or cements stabilized RCBA material, age and cement in the age-dose studies, with the increase in cement dose, mechanical properties growth trends are similar. Compared to unconfined compressive strength and resilient modulus, splitting strength is much closed in terms of growth trends or Growth value at the cement doses or ages. Good Relevance correlation are existed among resilient modulus, compressive strength and splitting strength: ,RCA: .

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.021
GPT teacher head0.253
Teacher spread0.231 · 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
Published2009
Admission routes1
Has abstractyes

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