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Record W2074184626 · doi:10.1021/es0112487

Radioactivity near the Sunken Submarine “Kursk” in the Southern Barents Sea

2002· article· en· W2074184626 on OpenAlexafffund
Г.Г. Матишов, D. G. Matishov, Alexey E. Namjatov, J. N. Smith, JoLynn Carroll, Salve Dahle

Bibliographic record

VenueEnvironmental Science & Technology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsBedford Institute of Oceanography
FundersUniversity of Toronto
KeywordsSubmarineOceanographyGeologyEnvironmental science

Abstract

fetched live from OpenAlex

Radioactivity measurements were conducted on seawater, sediment, and biota samples collected in the vicinity of the Russian submarine "Kursk" in September, 2000, within 1 month of the vessel's sinking in the Barents Sea to determine whether leakage of radioactivity from the vessel's two nuclear reactors had occurred and to assess the impact on one of the most productive fishing areas in the world. Levels of radioactivity in surface sediments and biota are within the range of values previously measured in the Barents Sea and can be ascribed to inputs from global fallout, European nuclear fuel reprocessing facilities, and the Chernobyl accident. However, levels of 1291 in seawater in the Southern Barents Sea increased by 500% between 1992 and 2000, and the 129I/137Cs ratio increased by more than an order of magnitude during this time, owing to long-range transport of releases from reprocessing facilities at Sellafield (U.K.) and La Hague (France). Although these results indicate that, at the time of sampling, leakage from the Kursk had a negligible impact on the environment, they also show that regional background levels of artificial radioactivity are varying rapidly on annual timescales and that Europe's nuclear reprocessing facilities are the leading contributor of anthropogenic radioactivity to the region.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.008
GPT teacher head0.197
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

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

Citations18
Published2002
Admission routes2
Has abstractyes

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