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Record W3211090550 · doi:10.3390/su132111881

Developments in Tall Wood and Hybrid Buildings and Environmental Impacts

2021· article· en· W3211090550 on OpenAlexafffund
Asif Iqbal

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Northern British Columbia
FundersStructural Timber Innovation CompanyAustralian GovernmentFPInnovationsUniversity of Canterbury
KeywordsUrbanizationClimate changeSustainabilityPopulation growthPopularityPopulationNatural resource economicsEngineeringEnvironmental scienceBusinessEnvironmental planningEconomicsEcologyEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Wood has been gaining popularity as a building material over the last few decades. There has been significant progress in technology during this period to push the limits of wood construction. At the same time, it has become more economically competitive to build with wood beyond low-rises. As a result, there has been a noteworthy shift in public perception in terms of acceptance of wood as a material for high-rise buildings. There is a growing list of tall wood buildings that have been constructed in different continents over the last decade. With worldwide population growth and increased urbanization, the trend is expected to continue. Considerable urgency for using sustainable resources to tackle the threat of climate change has resulted in a surge in demand as well as applications in recent decades. This paper reviews the significant technical advances that have contributed to those achievements and are expected to facilitate further developments.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.398

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 integrity0.0000.000
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 head0.003
GPT teacher head0.178
Teacher spread0.175 · 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 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

Citations31
Published2021
Admission routes2
Has abstractyes

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