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Record W2994437692 · doi:10.1029/2019gl084965

Foraminifera Trace Anthropogenic CO<sub>2</sub> in the NW Atlantic by 1950

2019· article· en· W2994437692 on OpenAlexafffund
Stefanie Mellon, Markus Kienast, Christopher K. Algar, Peter de Menocal, Markus Kienast, Thomas M. Marchitto, Matthias Moros, Helmuth Thomas

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsDalhousie University
FundersEnvironment and Climate Change CanadaCanadian Meteorological and Oceanographic SocietyNatural Sciences and Engineering Research Council of CanadaMarine Environmental Observation Prediction and Response Network
KeywordsForaminiferaOceanographyClimate changeEnvironmental scienceGeologyIsotopes of carbonOcean currentδ13CTotal organic carbonStable isotope ratioEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract The Northwest Atlantic is a region of major climate change over the twentieth century, affected by the weakening of the Atlantic meridional overturning circulation. To assess whether the ability of this region to absorb anthropogenic CO2 has been impacted by this change, we present the region's first long‐term carbon isotope (δ13C) time series of fossil foraminifera spanning the past 4,000 years. These records reveal an unprecedented negative δ13C excursion driven by anthropogenic CO2 penetration into the surface ocean, the “Suess effect” signal. This signal (amplitude −0.45‰) emerges in 1950 CE ± 15 with a decrease rate of 0.009 ± 0.001‰/yr. This marine signal is ~30% of the atmospheric Suess effect and emerges over a century later. Based on current estimates of the ratio of δ13CDIC change to dissolved inorganic carbon change and limited constraints on surface ocean residence times, we calculate a mean anthropogenic CO2 uptake rate of 0.6 ± 0.2 μmol/(kg yr) from 1950 to 2005.

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)0.000
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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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

Citations16
Published2019
Admission routes2
Has abstractyes

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