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Record W2123197653 · doi:10.1029/2010eo260001

Arctic Landscapes in Transition: Responses to Thawing Permafrost

2010· article· en· W2123197653 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.

Bibliographic record

VenueEos · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change Canada
FundersLos Alamos National LaboratoryInternational Arctic Research Center, University of Alaska, Fairbanks
KeywordsPermafrostTundraArcticErosionCoastal erosionWetlandClimate changePhysical geographySedimentThermokarstLandformGeologyArctic vegetationTree lineOceanographyEnvironmental scienceHydrology (agriculture)GeographyGeomorphologyEcology

Abstract

fetched live from OpenAlex

Observations indicate that over the past several decades, geomorphic processes in the Arctic have been changing or intensifying. Coastal erosion, which currently supplies most of the sediment and carbon to the Arctic Ocean [ Rachold et al. , 2000], may have doubled since 1955 [ Mars and Houseknecht , 2007]. Further inland, expansion of channel networks [ Toniolo et al. , 2009] and increased river bank erosion [ Costard et al. , 2007] have been attributed to warming. Lakes, ponds, and wetlands appear to be more dynamic, growing in some areas, shrinking in others, and changing distribution across lowland regions [e.g., Smith et al. , 2005]. On the Arctic coastal plain, recent degradation of frozen ground previously stable for thousands of years suggests 10–30% of lowland and tundra landscapes may be affected by even modest warming [ Jorgenson et al. , 2006]. In headwater regions, hillslope soil erosion and landslides are increasing [e.g., Gooseff et al. , 2009].

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 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 score0.131
Threshold uncertainty score0.988

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)0.0130.001

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 head0.248
Teacher spread0.224 · 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