Sedimentology and Structure of the Lake Palcacocha Laterofrontal Moraine Complex in the Cordillera Blanca, Peru
Bibliographic record
Abstract
The contemporary retreat of tropical glaciers in the Cordillera Blanca mountain range of Peru has resulted in the widespread formation of morainedammed glacial lakes. As continued glacial melt causes these lakes to grow in size, they pose the risk of unleashing glacial lake outburst floods (GLOFs), mass-wasting events that involve rapid lake drainage facilitated by a breach in the moraine dam. In 1941, a breach in the moraine dam at Lake Palcacocha produced a GLOF that killed close to 2000 people in the city of Huaraz. Current hazard assessment criteria for GLOF occurrence do not fully reflect the role of internal moraine structure in GLOF mitigation. Field observations of the sedimentology and structure of the Lake Palcacocha moraine have allowed a sequence of events for the genesis and evolution of the moraine to be proposed. The depositional conditions under which the Lake Palcacocha moraine developed gave rise to specific sedimentological structures within the moraine that could play a role in determining its resistance to failure. A thorough understanding of the processes governing moraine formation in the Cordillera Blanca is critical for modelling the development of both past and future moraines. These models can be applied to better understand the formation and stability of moraine dammed glacial lakes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".