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Record W3026655157 · doi:10.1002/ppp.2051

The distribution and dynamics of aufeis in permafrost regions

2020· article· en· W3026655157 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePermafrost and Periglacial Processes · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaWilfrid Laurier UniversityGovernment of Northwest Territories
FundersRussian Foundation for Basic ResearchW. Garfield Weston Foundation
KeywordsPermafrostClimate changeScale (ratio)Physical geographyTerminologyEnvironmental scienceDistribution (mathematics)Field (mathematics)Earth scienceGeologyClimatologyGeographyCartographyMathematics

Abstract

fetched live from OpenAlex

Abstract Aufeis, also known as an icing or naled, is an accumulation of ice that forms primarily during winter when water is expelled onto frozen ground or ice surfaces and freezes in layers. Process‐oriented aufeis research initially expanded in the 20 th century, but recent interest in changing hydrological conditions in permafrost regions has rejuvenated this field. Despite its societal relevance, the controls on aufeis distribution and dynamics are not well defined and this impedes projections of variation in aufeis size and distribution expected to accompany climate change. This paper reviews the physical controls on aufeis development, current broad‐scale aufeis distribution and anticipated change, and approaches to aufeis investigation. We propose an adjustment to terminology to better distinguish between the formation process and resulting ice bodies, a clarification of the aufeis classification approach based on source water, and a size threshold for broad‐scale aufeis inventory to facilitate collaborative research. We identify additional objectives for future research including advancing process knowledge at fine spatial scales, describing broad‐scale distribution using current remote sensing capabilities, and improving our understanding and predictive capacity over the interactions between aufeis and landscape‐scale permafrost, hydrogeological, geotectonic, and climate conditions.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.995

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)0.0000.000

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 head0.017
GPT teacher head0.215
Teacher spread0.197 · 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