Bibliographic record
Abstract
The life cycle performance of any infrastructure should be taken into consideration in its design, its construction, its maintenance, its operation, and when needed, its rehabilitation. The protection of infrastructure must be holistic, taking into account long-term socioeconomic and environmental considerations and the impact of the global climate change. Fulfilling the requirements of the ultimate and serviceability limit states over the service life of the facility requires an understanding of the use of the system, the deterioration response of the materials and their components when subjected to aggressive environments, and how this deterioration can be prevented or significantly delayed by preventive, remedial, and routine maintenance. The composition, microstructure, macrostructure, and various modes of deterioration of materials used in construction (steel, wood, concrete) are reviewed, along with possible remedial measures. The development of concrete as a construction material, its durability, and the relevant durability provisions in the various Canadian Standards Association standards are reviewed briefly. Current European practice and the 1990 Comité Euro-International du béton Design Guide for Durable Concrete Structures are evaluated. The engineer's responsibility for durable performance of a facility and the importance of durability audits are also examined.Key words: aggressive environment, construction materials, deterioration, durability, durability audits, life cycle performance, macrostructure, microstructure, socioeconomic and environmental considerations, sustainability.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".