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Record W2900887364 · doi:10.5539/mas.v12n12p28

Evaluation of a Warm Mix Asphalt Manufactured with Blast Furnace Slag

2018· article· en· W2900887364 on OpenAlexvenueno aff
Hugo Rondon Quintana, Saieth Baudilio Chaves-Pabón, Diego A. Escobar

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersUniversidad Militar Nueva GranadaUniversidad Nacional de Colombia
KeywordsAsphaltMaterials scienceMoistureAggregate (composite)Ground granulated blast-furnace slagComposite materialAsphalt pavementAbrasion (mechanical)Slag (welding)MetallurgyCement

Abstract

fetched live from OpenAlex

The study evaluated the response under monotonic loading (Marshall and indirect traction) and the resistance to moisture damage and abrasion of a warm mix asphalt (WMA) manufactured with an additive called HUSIL, when the coarse fraction of the aggregate was replaced by a blast furnace slag (BFS). In conclusion, it is reported that the additive is capable of reducing the manufacturing temperature of the asphalt mixture by 30 ° C. Additionally, the BFS can be used as a partial substitute for the coarse fraction of aggregates in WMA, since when replacing it in 21%, the mixture reach a significant increase in stiffness, resistance to moisture damage, and similar resistance to abrasion with respect to the control asphalt mixture.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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