Performance enhancement of RC structures through concrete jacketing: A structural rehabilitation approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Concrete buildings are facing some serious issues around the world. There are a few reasons for this, natural disasters such as earthquakes, lack of knowledge about important building codes, and poor supervision during construction. Because of these problems, many buildings are weaker than they should be. If these structures are under too much weight, they can bend and corrode, which means immediate repairs are needed. To tackle these problems with reinforced concrete, repair and strengthening methods have become really important in construction today. Even new buildings sometimes end up needing fixes because of design mistakes or problems during building. Structures that have been damaged by unexpected events like fires or earthquakes need special techniques to make them strong again. Fixing up buildings helps protect them from earthquakes and reduces the risk of damage. It's all about boosting a building's strength to meet safety standards. Many studies have looked into effective ways to reinforce them. This paper will take a brief look at some new and cost-effective methods for repairing damaged buildings.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it