Estudo do uso da madeira e sua relação com a sustentabilidade no setor da construção civil
Bibliographic record
Abstract
The planet Earth, throughout its period of existence, faces the consequences generated by climate change and the deterioration of the environment daily. Studies show that this aggravation can be caused by human activities, such as the deforestation of forests, which in the vast majority comes from anthropic actions in the livestock sector, agriculture and illegal extraction of wood, such actions produce significant emissions of greenhouse gases, boosting global warming. To contain these emissions, it is necessary to include activities such as reforestation and forest management, as they carry out the carbon sequestration, to reduce its concentration in the atmosphere. One of the sectores that exerts great influence on the quality of the environment is civil construction, throughout its construction process, from the beginning of the extraction of raw materials to its destination. One of the materials present in this market is wood, although little used in masonry for sealing buildings in Brazil, it has been present in society since ancient times, in the construction of shelters at the time for protection from the bad weather and in the manufacture of boats. Wood has numerous benefits, including its ability to promote significant reductions in greenhouse gas emissions, through the absorption of carbon dioxide produced in the process of photosynthesis for tree growth. When compared to other conventional materials most used in construction, such as steel, wood stands out and proves to be a sustainable material with great constructive potential. The extraction of this raw material must be carried out through controlled forest management, concomitant with the obtaining certification, and this certification is necessary for both parties, so that the consumer is aware of the origin of the management and for the environment which will be an explored in a correct way, assuring its preservation. In addition to the positive impact that the use of wood brings to a sustainable environment development, there is also economic development, through the carbon credit market, which includes projects aimed at reducing global emissions, contributing significantly to the country's revenue. Given this scenario, it is visible in many countries worldwide, such as Norway and Canada, the incentive and use of wood as a constructive raw material, on the other hand, here in Brazil, there is still the thought that this material is inferior to other traditional materials. Therefore, there is a need for a change of mentality both in society and the construction industry, so that there is an increasing application and evolution of the use of wood in the construction of buildings within the Brazilian construction market.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".