MASONRY PANEL TESTING IN MALAWI
Bibliographic record
Abstract
A holistic seismic risk management framework for East Africa, with particular focus on Malawi, is under development as part of the EPSRC-sponsored Global Challenges (GCRF) grant PREPARE. The project aims to co-produce practical tools and guidelines for enhanced disaster preparedness in close partnerships with local governmental and academic institutions. For the seismic vulnerability assessment of masonry buildings in Malawi, a series of tests were conducted in the field and in the Civil Engineering laboratory of the Malawi Polytechnic in Blantyre. The specimens and applied loads are of three main types: (a) single bricks subjected to uniaxial compression and three-point bending; (b) masonry prisms subjected to compression, direct tension and interface shearing; and (c) masonry panels of different brick configurations and reinforcement subjected to in-plane compression/shearing and out-of-plane bending in two planes. The specimens were built by local artisans using locally produced materials to simulate actual field conditions and indigenous construction methods. The different kinds of reinforcement tested were inspired by the recommendations of the Safer House Construction Guidelines of Malawi. Focusing on the masonry panel tests in (c) above, the main results from the experimental program are presented herein. The results help quantify the effect of simple, available types of retrofitting/reinforcing of masonry houses in Malawi.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".