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Record W3000718560 · doi:10.1029/2019gl086421

Two Decades of Ocean Acidification in the Surface Waters of the Beaufort Gyre, Arctic Ocean: Effects of Sea Ice Melt and Retreat From 1997–2016

2020· article· en· W3000718560 on OpenAlexaffabout
Y. Zhang, Michiyo Yamamoto‐Kawai, William J. Williams

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsAragoniteOceanographyCanada BasinSea iceGeologyOcean acidificationArctic sea ice declineArctic ice packAntarctic sea iceArcticOcean gyreSeawaterEnvironmental scienceCalciteMineralogy

Abstract

fetched live from OpenAlex

Abstract Anthropogenic CO2 uptake drives ocean acidification and so decreases the calcium carbonate (CaCO3) saturation state (Ω). Undersaturation of surface water with respect to aragonite‐type CaCO3 was first reported for 2008 in the Canada Basin, preceding other open ocean basins. This study reveals interannual variation of Ω in the surface Canada Basin before and after 2008. A rapid decrease of Ω occurred during 2003–2007 at a rate of −0.09 year−1, 10 times faster than other open oceans. This was due to melting and retreat of sea ice, which diluted surface water and enhanced air‐sea CO2 exchange. After 2007, Ω did not further decrease, despite increasing atmospheric CO2 and continued sea ice retreat. A weakened dilution effect from sea ice melt and stabilized air‐sea CO2 disequilibrium state is the main reason for this stabilization of Ω. Aragonite undersaturation has been observed for the last 11 years, and aragonite‐shelled organisms may be threatened.

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 score0.315
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.023
GPT teacher head0.268
Teacher spread0.246 · 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

Citations66
Published2020
Admission routes2
Has abstractyes

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