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Record W2171130757 · doi:10.14430/arctic44

Modern Erosion Rates and Loss of Coastal Features and Sites, Beaufort Sea Coastline, Alaska

2009· article· en· W2171130757 on OpenAlexvenueno aff
Benjamin Jones, Kenneth M. Hinkel, Christopher D. Arp, Wendy R. Eisner

Bibliographic record

VenueARCTIC · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsCoastal erosionErosionContext (archaeology)BayPhysical geographyGeologyBeaufort scaleOceanographyThreatened speciesPeriod (music)GeographyArchaeologyGeomorphologyEcology

Abstract

fetched live from OpenAlex

This study presents modern erosion rate measurements based upon vertical aerial photography captured in 1955, 1979, and 2002 for a 100 km segment of the Beaufort Sea coastline. Annual erosion rates from 1955 to 2002 averaged 5.6 m a-1. However, mean erosion rates increased from 5.0 m a-1 in 1955–79 to 6.2 m a-1 in 1979–2002. Furthermore, from the first period to the second, erosion rates increased at 60% (598) of the 992 sites analyzed, decreased at 31% (307), and changed less than ± 30 cm at 9% (87). Historical observations and quantitative studies over the past 175 years allowed us to place our erosion rate measurements into a longer-term context. Several of the coastal features along this stretch of coastline received Western place names during the Dease and Simpson expedition in 1837, and the majority of those features had been lost by the early 1900s as a result of coastline erosion, suggesting that erosion has been active over at least the historical record. Incorporation of historical and modern observations also allowed us to detect the loss of both cultural and historical sites and modern infrastructure. U.S. Geological Survey topographic maps reveal a number of known cultural and historical sites, as well as sites with modern infrastructure constructed as recently as the 1950s, that had disappeared by the early 2000s as a result of coastal erosion. We were also able to identify sites that are currently being threatened by an encroaching coastline. Our modern erosion rate measurements can potentially be used to predict when a historical site or modern infrastructure will be affected if such erosion rates persist.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.130
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.022
GPT teacher head0.242
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations85
Published2009
Admission routes1
Has abstractyes

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