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Record W2617574499 · doi:10.12737/5679

Definition of causes of destruction of materials of a bricklaying on sites of facades of buildings under construction of the residential quarter in the residential district "October" of Novocherkassk of the Rostov region.

2014· article· en· W2617574499 on OpenAlexaboutno aff
Анатолий Субботин, Anatoliy Subbotin, Виталий Субботин, Vitaliy Subbotin, Игнат Субботин

Bibliographic record

VenueConstruction and Architecture · 2014
Typearticle
Languageen
FieldMaterials Science
TopicStructural mechanics and materials
Canadian institutionsnot available
Fundersnot available
KeywordsCladding (metalworking)MasonryQuarter (Canadian coin)Architectural engineeringForensic engineeringEngineeringCivil engineeringMaterials scienceGeographyComposite materialArchaeology

Abstract

fetched live from OpenAlex

IThis article discusses the problem related to the appearance of defects in masonry cladding layer self-supporting walls of buildings with monolithic concrete frame for example inspection of buildings under construction of residential quarters in the October district of Novocherkassk. As a result of the survey by OOO "STC" identified and described the characteristic defects in the veneering layer self-supporting walls of buildings and identify their causes. Based on the experience of experts, instrumental studies of structural materials, conducted by a certified testing laboratory in materials survey gives an overview of the causes of defects are manifestations of research of other spe-cialists and organizations leading of which is CNIISK. VA Kucherenko. According to the results of the system analysis of detected defects and data instrumental studies, the authors proposed solutions to eliminate the defects and bring the building up to standard.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.248
Teacher spread0.221 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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