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Record W1485437487

Evaluación de mezclas arcillas con adición de tobas vítreas para la fabricación ladrillos cerámicos Bayamo

2015· article· es· W1485437487 on OpenAlexaboutno aff
Adrián Díaz Álvarez

Bibliographic record

VenueCiencia & Futuro · 2015
Typearticle
Languagees
FieldComputer Science
TopicEngineering and Information Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Se realizo el estudio de una mezcla compuesta por arcilla y tobas vitreas para la produccion de ladrillos, en La Canada; provincia Granma, para su posible utilizacion en la Industria de Materiales de la Construccion, utilizando esta como aditivo para los ladrillos de barro; a partir de sus propiedades fisico-mecanicas. Para ello se caracterizaron los materiales de acuerdo a su composicion quimica y sus propiedades fisicas. Se elaboraron 36 probetas de las cuales se hicieron 9 con un contenido de arcilla solamente y las restantes con 10, 15 y 20 % de aditivo tobas vitreas respectivamente, las cuales se sometieron a ensayos de contraccion natural, peso, absorcion de agua y resistencia a la compresion mecanica para determinar el comportamiento fisico mecanico en cada una de las probetas durante todo el paquete tecnologico. Se comprueba que la mas eficiente es la muestra a la que se le anadio un 10% de aditivo, porque absorbe mayor cantidad de agua y es mas resistente a la compresion, por lo tanto el ladrillo presenta una vida util mas larga.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.286
Teacher spread0.261 · 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
Published2015
Admission routes1
Has abstractyes

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