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Record W6996815093

Temporal variability of the anthropogenic CO2 storage in the Irminger Sea

2008· article· en· W6996815093 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Archive of Ifremer (French Research Institute for Exploitation of the Sea) · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsnot available
Fundersnot available
KeywordsOcean gyreNorth Atlantic oscillationStratification (seeds)SeawaterSea surface temperatureNorth Atlantic Deep Water
DOInot available

Abstract

fetched live from OpenAlex

The anthropogenic CO2 (C-ant) estimates from cruises spanning more than two decades (1981-2006) in the Irminger Sea area of the North Atlantic Subpolar Gyre reveal a large variability in the C-ant storage rates. During the early 1990's, the C-ant storage rates (2.3 +/- 0.6 mol C m(-2) yr(-1)) doubled the average rate for 1981-2006 (1.1 +/- 0.1 mol C m(-2) yr(-1)), whilst a remarkable drop to almost half that average followed from 1997 onwards. The C-ant storage evolution runs parallel to chlorofluorocarbon-12 inventories and is in good agreement with C-ant uptake rates of increase calculated from sea surface pCO(2) measurements. The contribution of the Labrador Seawater to the total inventory of C-ant in the Irminger basin dropped from 66% in the early 1990s to 49% in the early 2000s. The North Atlantic Oscillation shift from a positive to a negative phase in 1996 led to a reduction of air-sea heat loss in the Labrador Sea. The consequent convection weakening accompanied by an increase in stratification has lowered the efficiency of the northern North Atlantic CO2 sink.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.086
GPT teacher head0.319
Teacher spread0.232 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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