Design Characteristics that Achieve the Factor of Safety and Security from Fire Accidents for Users of Administrative Buildings
Bibliographic record
Abstract
The need for safety and security is one of the important human needs, as it comes in second place after the basic human needs according to Mauslow's hierarchy of human needs. Therefore, achieving the safety and security factor in the design of buildings is considered one of the important design factors, which must occupy an important space in the architectural designer's thought from the early stages of design until the completion of the design in all its details, because the issue is related to the safety of lives and property. The research adopted the theoretical analytical approach by reviewing the studies and literature that dealt with the topic of research then analyzing them to achieve the objective of the research in reaching a clear and comprehensive classification of design characteristics (architectural and non-architectural) that achieve the factor of safety and security from fire accidents for users of administrative buildings, in addition to classifying these characteristics based on their relationship to the stages of the design process. The results of the research were in the form of a clear and comprehensive table of the above design characteristics, which are design characteristics that contribute to preventing the occurrence of fire, and characteristics that reduce fire damage when it occurs (characteristics that help contain fire and characteristics that facilitate the arrival of firefighters to fight the fire and characteristics that help in the speedy evacuation of building users). The research also reached a set of conclusions, and the results, conclusions reached by the research can be used as a guide for architectural designers and specialists in the field of safety to design administrative buildings that achieve safety and security from fire accidents for their users.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".