Firebrand generator system applied to wildland-urban interface research
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
The problem of forest fires in the Wildland Urban Interface (WUI) areas is increasing in all countries that have problems with forest fires. This phenomenon is well known and studied in USA, Canada or Australia. In European countries the problem is identified and studied. In the last 50 years Portugal experienced an unprecedented rural exodus in all its history. Rural areas faced the decreasing of population every year on the one hand emigration, on the other hand young people moved to urban areas. This led to difficulties of management and increased problems related with combat of wildland fires. The problem of WUI is growing so fast in Portugal in last decade, mainly as a result of the events occurred in 2003, 2005, recently 2012 and 2013. This problems of WUI were identified as a priority, immediately afterwards to personal safety. Given the importance of spot fires in the context of WUI fires the Centre of Forest Fire Studies (CEIF) developed several studies to increase the knowledge on this problem. A study of the probability of penetration of firebrands in typical Portuguese house roofs was carried out. Studies on ember aerodynamic transport and on new ignitions inside houses caused by embers. In particularly this second work about ignitions inside houses is being developed with test that involves the generation of embers in a special device designed to create embers, similar to the ones generated in a real forest fire that can transpose structural gaps of the models tested and start a new fire inside of the structure. In order to carry out this study program a firebrand generator similar to the Baby Dragon developed at NIST by Suzuki and Manzello in 2011 was built. The original device was used in 2013 by Manzello for a similar study.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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