Key Point of Bridge Damage Caused by Glacial Debris Flows along International Karakorum Highway, Pakistan
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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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".