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Record W4319791815 · doi:10.1111/bor.12611

Landsystem analysis of a tropical moraine‐dammed supraglacial lake, Llaca Lake, Cordillera Blanca, Perú

2023· article· en· W4319791815 on OpenAlexafffund
Rodrigo A. Narro Pérez, Carolyn H. Eyles, Rebecca E. Lee, Luzmila Dávila, John C. Maclachlan

Bibliographic record

VenueBoreas · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMoraineGeologyLandformGlacierGeomorphologyPhysical geographyRock glacierSedimentTerminal moraineBedrockGeography

Abstract

fetched live from OpenAlex

Tropical glaciers of the Cordillera Blanca, Perú are rapidly thinning and retreating as a result of climate warming. The retreat of these glaciers along narrow linear bedrock valleys has increased the number and size of moraine‐dammed glacial lakes formed in the valleys. This study aims to identify the geomorphological and sedimentological characteristics of an enlarging moraine‐dammed supraglacial lake (Llaca Lake) in the Cordillera Blanca. Field‐based sedimentological observations and geomorphological mapping were combined with remotely sensed data and a photogrammetric model derived from aerial surveys by an uncrewed aerial vehicle to identify landform‐sediment assemblages. The geomorphological and sedimentological characteristics of Llaca Lake are synthesized into three landsystem zones: Zone 1: distal portions of Llaca Lake and the latero‐frontal moraine; Zone 2: the central zone of ice‐cored hummocks; and Zone 3: the active glacier margin. These zones are differentiated based on the spatial distribution of landforms, sediments, and active geomorphological processes. This is the first study to describe the landform‐sediment assemblages in a tropical moraine‐dammed supraglacial lake system and provides a framework for further landsystem element analysis of these growing supraglacial lakes in rapidly deglaciating high‐altitude environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.024
GPT teacher head0.233
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

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