MétaCan
Menu
Back to cohort
Record W4405543946 · doi:10.35784/bud-arch.6619

Control of building safety through snow load monitoring

2024· article· en· W4405543946 on OpenAlexaff
Roman Kinasz, Wiesław Bereza

Bibliographic record

VenueBudownictwo i Architektura · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsSnowRoofEnvironmental scienceClearanceDeflection (physics)Computer scienceCivil engineeringEngineeringMeteorology

Abstract

fetched live from OpenAlex

Climatic loading in the form of snow load is a significant factor for building structures. This is relevant during the design stage, the execution stage, and especially throughout the operational period. Building owners are legally required to ensure that their roofs are cleared of snow, often raising the question of whether such action is necessary in a particular situation. To address this, various devices have been developed to facilitate the systematic monitoring and measurement of snow load on roofs. These devices measure snow weight either indirectly or directly. The methods for monitoring snow weight and evaluating the effect of snow load on structural safety have been extensively discussed in the literature, considering aspects of structural integrity, operation under harsh conditions, and the economic implications of building management. In this paper, the authors propose an innovative approach to monitoring snow load using snow scales, supplemented by roof deflection measurements with tilt sensors (inclinometers). Such systems not only ensure the safety of the building and its occupants by providing reliable and verified results but also achieve this in a cost-effective manner.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.294
Teacher spread0.278 · 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 designOther design
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBudownictwo i ArchitekturaSame topicStructural Health Monitoring TechniquesFrench-language works237,207