Water for firefighting: A comparative study across several cities
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
Studies into water for firefighting are sparse in global literature. Over the past three decades, 6 published studies have been undertaken in South Africa to quantify the extent of municipal water employed to fight fires. These studies have been necessary considering the need to conserve scarce and dwindling freshwater resources while providing adequate fire protection to many South African communities. While these studies have been driven by similar objectives, their analysis have not produced results that can easily be compared in order to extract generic highlights that can aid national firefighting efforts. In addition, the recent firefighting studies postulate that the minimum fire flows in the South African National Standard (the SANS 10090) and Guideline (The Red Book) are conservative and therefore do not promote the appropriate design of water networks. This may be attributed to the fact that the fire flows in the 1st edition of the SANS 10090 were likely over-estimated for South Africa since they were compiled with the assistance of organisations from the UK, USA, Canada, New Zealand and Germany, and have not notably changed since. This paper therefore aims to address 2 objectives. The first objective will extract as much data as is possible from each of the 6 studies and will analyse the data with the aim of comparing consistent parameters (such as fire flows). The second objective will compare results obtained from the first objective with the SANS 10090, The Red Book and available international Standards and Guidelines for firefighting. Based on the results from the second objective, this study will conclude on the appropriateness of the minimum fire flows in the SANS 10090 and The Red Book to current firefighting efforts.
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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 | 0.000 |
| 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