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Record W7145523106

Temporal changes in iodine-129 and radiocesium in the Canada Basin in the Arctic Ocean between 1993 and 2020

2024· article· en· W7145523106 on OpenAlexaboutno aff
Kumamoto Yuichiro, Hamajima Yasunori, Nishino Shigeto, Inoue Mutsuo, NAGAI Hisao, Matsuzaki Hiroyuki, Yamagata Takeyasu, MURATA Akihiko, Kikuchi Takashi

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsArcticSubarctic climateArctic dipole anomalyStructural basinCanada BasinBiogeochemical cycleThermohaline circulationClimate changeOcean current
DOInot available

Abstract

fetched live from OpenAlex

The Arctic Ocean plays an important role in global climate and global warming through freshwater and heat exchange with subarctic waters. A better understanding of circulation time scales in the Arctic Ocean is essential to predict changes in climate and biogeochemical cycling in the Arctic Ocean. 129I and 137Cs, which have been discharged from the nuclear fuel-reprocessing facilities, have been employed to determine the time scale of the circulation in the Arctic Ocean. However, its temporal change has not been understood well. In 2017, 2019, and 2020, we measured 129I and 137Cs in the Canada Basin in the Arctic Ocean. Using our new and historical data, we discuss temporal changes in the circulation in the basin between 1993 and 2020. The tracer ages derived from the 129I/137Cs ratio indicate that the transport of the Atlantic water into the Canada Basin was accelerated in 2020. This is consistent with results of recent studies that indicated the intensified inflow of the Atlantic water into the eastern Arctic Ocean in the late 2010s, which is termed “atlantification”. Our results confirmed the “atlantification” in the Canada Basin by temporal changes in the transient tracers for the first time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueInstitutional Repositories DataBase (IRDB)Same topicArctic and Antarctic ice dynamicsFrench-language works237,207