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Record W1967280089 · doi:10.15628/holos.2011.524

PROPRIEDADES TECNOLÓGICAS DE BLOCOS SÍLICO CALCÁRIOS INCORPORANDO RESÍDUO CALCÁRIO

2011· article· pt· W1967280089 on OpenAlexaff
Alex Micael Dantas de Sousa, Dárcia Sâmia Santos Moura, Márcio Luiz Varela

Bibliographic record

VenueHolos · 2011
Typearticle
Languagept
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesChemistryPhilosophy

Abstract

fetched live from OpenAlex

Um dos fundamentos da realização desta pesquisa refere-se à possibilidade de minimizar os impactos ambientais decorrentes da exploração da rocha calcária. Nesta vertente, esta pesquisa apresenta um estudo de caráter experimental voltado à incorporação de resíduo calcário em formulações de blocos sílico-calcários para alvenaria estrutural, avaliando a viabilidade técnica de produção destes através da determinação de suas propriedades físico-mecânicas, representadas nesta pesquisa pela retração linear de cura, absorção de água, porosidade aparente, massa específica aparente e módulo de ruptura à flexão em três pontos. Ao término do estudo acerca da incorporação do resíduo nos blocos, foi constatado que torna-se inviável a sua utilização como agente aglomerante na mistura, tendo em vista que não propicia a formação de silicato hidratado de cálcio na mistura, o que resulta em valores pouco significativos no que concerne aos resultados das propriedades físico-mecânicas.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.232
Teacher spread0.188 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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