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Record W7009328807

Diseño de mezcla de concreto translúcido aplicando agregados que permiten el paso de luz, Lima – 2021

2022· dissertation· en· W7009328807 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2022
Typedissertation
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsGlass recyclingCementAggregate (composite)Work (physics)Block (permutation group theory)
DOInot available

Abstract

fetched live from OpenAlex

The objective of this work is to carry out a mix design for translucent concrete using aggregates that allow the passage of light, therefore, an analysis related to the translucent concrete mix design was carried out, in a time interval of 10 years, to define what type of aggregates, additives and w/c ratio, are the ones that will provide the greatest benefit to the final product. For this, a mix design for translucent concrete was proposed, referring to ACI 211.1, since different aggregates such as tempered glass, quartz, white cement and also a plasticizing additive will be used to obtain an optimal design for translucent concrete. In addition, application cases with additive were carried out, in order to obtain different mix designs with the properties of translucency and resistance to compression, with these designs it was concluded that quartz and Ottawa sand are the aggregates that most favor the passage of light, however, using glass at 40% and quartz at 60% in the mix design gives moderate translucency to the mix, finally it was defined that the possible applications of this type of concrete are given for glass block type partitions and false ceiling , that is, for non-bearing aesthetic structures.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.211
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.250
Teacher spread0.244 · 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.

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
Published2022
Admission routes1
Has abstractyes

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