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Record W3189259074 · doi:10.1002/esp.5212

Antecedent controls on the spatial organization of yardangs on the Puna Plateau, north‐western Argentina

2021· article· en· W3189259074 on OpenAlexafffund
Elena A. Favaro, Chris H. Hugenholtz, Thomas E. Barchyn

Bibliographic record

VenueEarth Surface Processes and Landforms · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaDigitalGlobe FoundationGeological Society of America
KeywordsGeologyAeolian processesMars Exploration ProgramAridLandformAntecedent (behavioral psychology)GeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Abstract Yardangs are streamlined ridges that form in arid environments on Earth and Mars through wind‐driven abrasion of consolidated substrates. Currently, there is limited consensus on the mechanisms that initiate and establish patterns of yardangs on the landscape. In this work, we examine the spatial organization of yardangs in the Campo de Piedra Pómez ignimbrite deposit of north‐western Argentina and identify evidence of antecedent controls on yardang patterns and formation. We mapped 14,826 yardangs in the region using a high‐resolution digital elevation model (DEM) and satellite imagery. We classified yardangs as points using a two‐stage decision rule based on morphology and spectral characteristics. Point pattern analysis shows that yardangs in the study area are not randomly distributed and commonly exhibit directional anisotropy in point pattern. The anisotropic pattern manifests as bands of closely‐spaced yardangs oriented transverse to the dominant northwesterly wind direction. We hypothesize that banding is controlled by pre‐existing antecedent topography in the bedrock, such as fumaroles or ridges associated with pyroclastic flow deposits. We present evidence from other locations on Earth and Mars to illustrate that the transverse banding is a common pattern in yardang landscapes.

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 score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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
Published2021
Admission routes2
Has abstractyes

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