Safety assessment of the Qinghai–Tibet railway: Monitoring, analysis, and prediction
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 temporal and spatial evolution regularity of the surface along the Qinghai–Tibet railway (QTR) have been examined, and intelligently sensing the potential risks is of considerable importance to its safe operation. 1166 Sentinel-1 A images from Jan. 2017 to Apr. 2023 were collected to obtain·1956 km of surface deformation along the QTR using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique. Satellite + UAV multi-scale 3D modeling was used with Beijing 3 (BJ-3) satellite images and key tunnel entrance drone images. Risk assessment of key geologic hazards and 3D reality verification was performed along the QTR. The QTR surface deformation was unevenly scattered in space and the maximum annual deformation rates recorded were 26 mm/year. In the permafrost region, railway deformation settled at a constant rate in the warm season and rose slowly in the cold season. Under climate warming, the warm season gradually became longer than the cold season. Adding precipitation and temperature to the analysis showed that the deformation in permafrost regions had significant aggregation characteristics. A large deformation along the railway occurred, and human activities were frequent. The reliability of the InSAR technique was verified by using Global Navigation Satellite System (GNSS) reference data along QTR. InSAR results correlated strongly with GNSS data. The Tent Mapping Sparrow Search Algorithm Long Short-Term Memory (Tent-SSA-LSTM) was proposed to forecast the forthcoming deformation along the QTR to achieve early detection and early warning. Compared with the traditional prediction model, evaluation increased by 34.1 %, 40.1 %, and 36.3 %, respectively. The findings can provide a scientific foundation for pertinent government departments in rescue and disaster prevention. • Overview of SBAS-InSAR applications in permafrost railway studies. • Close correlation between precipitation/temperature and deformation in study area. • Evaluate the reliability of SBAS-InSAR technique by GNSS results. • Risk assessment of key geologic hazards was performed.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| 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