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Record W3130281131 · doi:10.2749/nantes.2018.s32-1

Hybrid CLT-Based Modular Construction Systems for Prefabricated Buildings

2018· article· en· W3130281131 on OpenAlexaff
Cristiano Loss, Thomas Tannert

Bibliographic record

VenueReport · 2018
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsModular designModular constructionPrefabricationArchitectural engineeringEngineeringFocus (optics)Construction engineeringCivil engineeringStructural engineeringComputer science

Abstract

fetched live from OpenAlex

Contemporary structures are required to be earthquake-resistant, sustainable and flexible to changing occupancy needs over time. Hybrid wood-based construction systems are promising solutions for modern buildings and research for cost-efficient systems is underway to compete with more traditional and widely spread non-wood building systems. This paper presents an innovative modular and prefabricated wood-based hybrid construction technology. It is a dry solution obtained by fastening on-site steel frames and composite CLT-steel members using only bolts and screws. The main results obtained from a comprehensive experimental programme with focus on the in-plane and out-of-plane behaviour of floors are reviewed. The influence of connections on the response of floors is discussed. The findings are of practical relevance with direct impacts on other applications.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.215
Teacher spread0.200 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

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