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Record W2089339079 · doi:10.1029/2006gl028543

Uptake of natural and anthropogenic carbon by the Labrador Sea

2007· article· en· W2089339079 on OpenAlexaboutno aff
F. Terenzi, Tim Hall, Samar Khatiwala, Christian Rodehacke, Deborah A. LeBel

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsAdvectionEnvironmental scienceDisequilibriumCarbon dioxideAtmospheric sciencesAtmosphere (unit)Carbon fibersCarbon dioxide in Earth's atmosphereGreenhouse gasCarbon cycleOceanographyGeologyMeteorologyClimate changeEcosystemChemistryEcologyGeographyMaterials science

Abstract

fetched live from OpenAlex

We apply to Classical Labrador Sea Water (CLSW) the transit‐time distribution (TTD) method to estimate the inventory and uptake of anthropogenic carbon dioxide (Cant). A model of TTDs representing bulk‐advection and diffusive mixing is constrained with CFC11 data. The constrained TTDs are used to propagate Cant into CLSW, allowing the air‐sea disequilibrium to evolve consistently. Cant in the Labrador Sea (LS) surface waters cannot keep pace with increasing atmospheric CO2 and is highly undersaturated. Our best estimate for 2001 is an anthropogenic inventory of 1.0 Gt C and an uptake of 0.02 Gt C/year. By additionally using the constraint of present‐day CO2 measurements, we estimate that the preindustrial LS was neutral or a weak source of CO2 to the atmosphere. Our estimates are subject to possible error due to the assumption of steady‐state transport and carbon biochemistry.

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 score0.097
Threshold uncertainty score0.194

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 communication0.0010.001
Open science0.0000.001
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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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

Citations30
Published2007
Admission routes1
Has abstractyes

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