A provisional fire risk characterization of informal settlements of different scales in San Jose, Costa Rica
Bibliographic record
Abstract
: This study gathers and explores qualitative information from four informal settlements within San Jose, Costa Rica, to help define future informal settlements’ fire safety research. In this paper, field visits to the four different settlements were conducted. Two of which are categorized as “large”, being over 0.50 km 2 , while the other two are “small” being between 0 and 0.25 km 2 . The physical differences and similarities observed in each settlement are considered with the aim to determine how these features might affect the fire risk and population response in case of a fire event. Through these visits, it was possible to conclude that informal settlements of similar size share several characteristics, while there is a clear difference between those of different sizes. The main differences and similarities were related to waste-management, proximity, type of construction of the houses, materials used, and organization within the community. This research also discusses current challenges faced by practitioners when performing informal settlements fire spread and evacuation modeling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".