Degradation of Concrete Structures from the Climate Change Perspective
Bibliographic record
Abstract
The negative effects of climate change are underway despite the global efforts to mitigate them and the future scenario are unsettling. Climate change poses critical challenges to urban environments and highlights the need for research its impacts on the built environment. One of the most significant effects of climate change on reinforced concrete structures is associated with the carbonation of these structures. The increase of parameters such as temperature and carbon dioxide jeopardise the degradation of such structures by carbonation-induced corrosion. This paper presents the results of the monitoring and analysis of a set of buildings that determine carbonation as the main degradation mechanism of structures in Paraguay. Through the application of a previously developed carbonation model, the worsening of the carbonation-induced degradation has been determined after considering the climate change effects in the coming 50 years. The outcomes of the study determined that the poor quality of the structures in Paraguay cause premature degradation in them. Furthermore, considering climate change effects, it has been determined that this phenomenon could accelerate corrosion failure times in reinforced concrete structures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".