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Record W4408990069 · doi:10.18280/acsm.490102

Study of the Characteristics of Kutai Kertanegara Local Quarry Stone for Self-Compacting Concrete Production

2025· article· en· W4408990069 on OpenAlexvenueno aff
Muhammad Noor Asnan, Rusandi Noor, Ni’matul Azizah Raharjanti, Eka Sri Wahyuni, H Hartono, Vebrian

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsMining engineeringProduction (economics)GeologyArchaeologyPulp and paper industryEngineeringGeographyEconomics

Abstract

fetched live from OpenAlex

Classification, abrasion, and compressive strength conditions of rocks can affect the quality of concrete and potentially cause damage/failure of building structures.This local rock research is needed for utilization as coarse aggregate in concrete mixtures.Rocks are located in 4 quarries in Kutai Kertanegara Regency.Each quarry was identified by taking rocks in the form of boulders and coarse aggregates.Rock samples were observed visually from a geological perspective and tested for physical and mechanical properties.Rock compressive strength test with cube-shaped samples measuring 5 x 5 x 5 cm.The compressive strength value of 50 MPa was continued to make high-quality SCC concrete samples in cylinders measuring 10 x 20 cm for each age of 3, 7, 14, 21, 28, 56, and 90 days.Then, the rock classification was obtained, including limestone, and it had many cracks.The average rock abrasion value was obtained at less than 40%.The compressive strength of the rock at location KM.45 was 64.89 MPa, KM.40 obtained 42.05 MPa, while other places did not meet the minimum value.The 28-day concrete compressive strength was obtained 28.662 MPa from the KM.45 location and 23.884 MPa from the KM.40 location.The development of concrete strength according to age shows a trend that does not increase and fluctuates.Compared to concrete, it generally shows a trend that continues to increase according to age.This condition indicates that the limestone has uneven or inconsistent strength, so it is unsuitable for high-quality concrete use.This information is expected to be a guideline for using local rocks.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.314

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 studies0.0000.001
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 head0.018
GPT teacher head0.257
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 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
Published2025
Admission routes1
Has abstractyes

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