Geomorphic Process Chains in High‐Mountain Regions—A Review and Classification Approach for Natural Hazards Assessment
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Populations and infrastructure in high mountain regions are exposed to a wide range of natural hazards, the frequency, magnitude, and location of which are extremely sensitive to climate change. In cases where several hazards can occur simultaneously or where the occurrence of one event will change the disposition of another, assessments need to account for complex process chains. While process chains are widely recognized as a major threat, no systematic analysis has hitherto been undertaken. We therefore establish new understanding on the factors that directly trigger or alter the disposition for subsequent events in the chain and derive a novel classification scheme and parameters to aid natural hazard assessment. Process chains in high mountains are commonly associated with glacier retreat or permafrost degradation. Regional differences exist in the nature and rate of sequencing—some process chains are almost instantaneous, while other linkages are delayed. Process chains involving rapid sequences are difficult to predict, and impacts are often devastating. We demonstrate that process chains are triggered most frequently by progressive failures, being the result of gradual landscape weakening and not due to the occurrence of a distinct process. If fluvial processes are part of the process chain the reach (or mobility) of process chains is increased. Increased mobility can also occur if sediment deposition areas along river channels are activated. As climate changes causes glacial environments to transform into sediment‐rich paraglacial and fluvial landscapes, it is expected that the mobility of process chains will increase in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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