Thai Tattoo Wisdom’s Representation of Knowledge by Ontology
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
Sak Yan Ontology (SYO) models knowledge derived from Thai tattoos in the design of cultural heritage preservation planning. Ontology Development 101 is a technique of ontology model creation. The aims of this study are to share the performance of ontology development and ontology evaluation. The study is specifically focused on validation from domain experts and automation evaluated using the OOPS! tools (OntOlogy Pitfall Scanner is a tool that helps detect some of the most common pitfalls appearing when developing ontologies). The results obtained from OOPS! show that SYO is devoid of critical errors; however, it does have one critical, three important, and three minor problems. Four of the problems are fixed, whereas the others are continuous. The combination of automatic and human validation methodologies improves the quality of the ontology being modeled. The tools enhance the traditional methodology with quicker, easier, and smaller amounts of subjective analysis. In conclusion, for the reparation movement, solutions for the above problems are suggested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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