BIBLIOMETRIC ANALYSIS ON THE EVOLUTION OF FIRE RESISTANCE IN TIMBER STRUCTURE
Bibliographic record
Abstract
The increasing demand for sustainable and fire-safe construction has drawn significant attention to the fire resistance of timber structures, yet a comprehensive overview of global research trends in this field remains limited. This study addresses this gap by conducting a bibliometric analysis to evaluate the development, patterns, and collaborations in fire resistance research related to timber. Data were collected through Scopus advanced searching using defined keywords, which yielded 402 relevant documents published between 2000 and 2025. The analysis employed the Scopus analyzer to generate statistical outputs and graphical trends, while OpenRefine was applied to clean and harmonize the dataset, ensuring accuracy and consistency in author names, keywords, and institutional affiliations. VOSviewer software was then used to perform network visualizations, including co-authorship, keyword co-occurrence, citation, and country collaboration mapping. The numerical results reveal a steady increase in publications over the last two decades, with a significant surge after 2015, indicating growing global recognition of timber's role in sustainable construction and the need for enhanced fire safety performance. China, Canada, and the United States emerge as the most productive contributors, while highly cited papers are concentrated in journals focusing on fire safety, structural engineering, and material science. Co-occurrence keyword analysis highlights recurring themes such as fire resistance, charring rates, cross-laminated timber, and fire protection strategies, which together demonstrate the field's evolution from fundamental testing toward advanced modelling and engineered wood applications. The findings contribute to the body of knowledge by identifying research gaps, highlighting leading countries and institutions, and emphasising international collaboration as a driver of innovation. Overall, this study provides a clear bibliometric overview of research trends in fire resistance of timber structures, supporting the advancement of safe, resilient, and sustainable construction practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.064 | 0.125 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".