Building Facade Failures due to Rainwater Entry in Turkey
Bibliographic record
Abstract
Abstract Facade failures due to rainwater entry are common in Turkey although, few systematic studies have been completed to determine the types of defects and failures and their causes as would permit developing appropriate repair solutions. The intent of this study is to determine the types of defects and failures caused by rainwater ingress to building facades based on case studies of failure in Turkey. Thus, defects and failures can be characterized and classified, such that the most common types of failure can be revealed and adequate repair solutions proposed. A review of literature was conducted of studies undertaken in Turkey on rainwater entry and building defects. Additionally, field inspections were carried out for 16 public buildings in Istanbul and information regarding failures was gathered from local authorities. Based on data evaluated from previous research and field inspections, it was determined that majority of the buildings had cladding walls with stucco being the most common cladding material. Failures occurred in cladding facades with stucco included detachment of cladding, staining, and cracks; the most common failure was blistering and exfoliation. Air and rainwater leakage due to defects in sealants was the most common failure in buildings with panel and stick wall systems.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".