A Safe Evacuation Mode for Ultradeep Underground Space in Urban Rail Transit Stations
Bibliographic record
Abstract
Recent years has seen the rapid development of rail transit and comprehensive development of underground and aboveground facilities. Against this backdrop, it is imperative to develop a suitable safe evacuation mode for ultradeep underground public spaces. From the perspective of building design, this paper combines the horizontal shelter and vertical evacuation system into a novel safe evacuation mode, consisting of horizontal evacuation, vertical escape route, emergency shelter, horizontal escape route, vertical evacuation system and exit evacuation. Then, building information modelling (BIM) was adopted to simulate the application of our safe evacuation mode to Hongtudi Station, Line 10 of Chongqing Rail Transit (CRT). The results prove that our safe evacuation mode is feasible for evacuating personnel in ultradeep underground public spaces. The research findings shed new light on the safe evacuation technology in ultradeep underground public spaces.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".