Conservation and Restoration Guidelines for the Omo Sebua in Bawömataluo Village, South Nias, Indonesia
Bibliographic record
Abstract
In recent years, wooden structures have been being gradually replaced by reinforced concrete and brick buildings. Although a conservation system has been established in Indonesia, specific conservation and repair guidelines for traditional wooden buildings have not been well-regulated. This paper takes the omo sebua as a research subject, aims to clarify the deterioration, deformation and their causes, and to propose guidelines for its conservation. The results of the deterioration and deformation investigation are as following: the maximum inclination of the short pillars is 5/100, and the most common inclination is 2/100. The significant sinkage of the foundation stones reaches 56 cm and the average sinkage is 20~30 cm. The maximum inclination of side pillars is 4/100, and the most common inclination is 2/100. Besides, the corruptions of the roof frame concentrate on the gable wall and termite damages can be seen in the whole building. Basing on the investigation result, our proposals are as following: 1) conduct a dismantling restoration; 2) recycle the used materials as much as possible to maintain the authenticity of the building; 3) use new materials that are the same as the original ones; 4) rethatch the roofing by sago palm leaf; 5) conduct a structural diagnose, reinforce the structure against an earthquake; 6) include electrical equipment and disaster management in a restoration.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".