An overview of circular economy for wooden construction
Bibliographic record
Abstract
Circular Economy(CE) is an economic concept, which is in the framework of sustainable development. Circular economy is mostly related to the use of material after their life cycle, and has to be implemented at the design stage of a product or a system. On the one hand, increasing the taxes and the expenses for waste disposal, and on the other hand, decreasing in the resources push industries forward in using circular economy. Nowadays due to the increase in the population, the need for shelter increase and among the materials, which can be used in building, wood is becoming more popular. As wood resources face depletion and wooden houses can have a long lifetime, there will be lots of possibilities for re-using the wooden parts. But as the types of wood for being used in different industries differ, selecting the best type of wood and the future use of it in other industries have to be considered in the buildings’ designing stage.In this work at first the structure and life cycle of the buildings were studied. After that, a new circular structure has been proposed by involving CE in the previous structure. Then by defining appropriate indicators, the use of wood as the main raw material for constructions evaluated. This evaluation has been done by the means of multi criteria decision-making(MCDM) methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".