Key Point of Bridge Damage Caused by Glacial Debris Flows along International Karakorum Highway, Pakistan
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
Glacial debris flows along International Karakorum Highway (KKH) connecting northern Pakistan with China, are always causing so extreme threats to a majority of bridges built along KKH. So the improvement project of KKH has been being carried out by China Road & Bridge Corporation in 2008. However it is necessary to collect the detailed data about the damages to bridges and obtain the most dangerous key position. The series of field investigations from 2008 to 2011 demonstrate that the damages are classified into four categories: deposition under bridge, abrasive erosion, impact on piers or abutment and collapse due to buoyancy. Statistics indicate deposition under bridge is the most dominant damage whereas the most serious damage is the impact on piers or abutments. Therefore a case study on key point is made for the typical bridge subjected to impact from Ghulkin glacial debris flow. Finally prevention measures are given.
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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) | 0.001 | 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 it