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Record W2939960144 · doi:10.29173/mocs62

Key technologies for prefabricated timber buildings

2017· article· en· W2939960144 on OpenAlexvenueno aff
Minjuan He, Jing Luo, Zheng Li

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsPrefabricationArchitectural engineeringKey (lock)Process (computing)EngineeringConstruction engineeringCivil engineeringComputer scienceComputer security

Abstract

fetched live from OpenAlex

Nowadays, Chinese government has enacted a series of regulations and policies to increase the prefabrication level in building constructions. Timber structures are featured by the characteristic of a high level of prefabrication. A lot of attention has been paid on the research and application of prefabricated timber buildings recently. This paper presents a brief introduction of the structural systems and key technologies for prefabricated timber buildings. A few case studies on multi-story timber or timber-hybrid buildings are analysed with the emphasis on introducing their structural system and the respective construction techniques. The objective is to provide selected examples to explore the possible strategies with the understanding that prefabricated construction is an organizational process based on a steady flow of stages of the whole construction process. The current knowledge gaps are identified and discussed, concerning the industrialization process and an increasing degree of assembling. Furthermore, future opportunities for prefabricated timber buildings have been put forward.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.894

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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