MétaCan
Menu
← Back to cohort

Transient Tracers and Anthropogenic Carbon in Central Labrador Sea: a Multi-Decadal Study

2020· article· en· W3196046409 on OpenAlexaffabout
Lorenza Raimondi, Kumiko Azetsu‐Scott, Toste Tanhua, Igor Yashayaev, Doug Wallace

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsBedford Institute of OceanographyDalhousie University
Fundersnot available
KeywordsTRACERTransectOceanographySeawaterEnvironmental scienceChemistryGeologyPhysics

Abstract

fetched live from OpenAlex

Over the last thirty years the Bedford Institute of Oceanography (BIO) has been maintaining the Atlantic Zone Off-Shore Monitoring Program (AZOMP), which includes annual occupation of several sections and stations in the Northwest Atlantic Ocean. Among these, the AR7W line across the Labrador Sea has one of the longest time-series where both transient tracers and dissolved inorganic carbon (DIC) have been collected since the early 1990s. Among multiple transient tracers that have been measured along this transect (CFC-11, CFC-113, CCl4 and SF6), only measurement of CFC-12 extends over the full time-series from 1992 to 2018, overlapping with DIC observations. Measurements of CFC-12 were also available for a previous cruise in 1986, extending the time-series to three decades. In this work we present the temporal variability of CFC-12 (1986-2016) and DIC (1992-2016) concentrations as well as their distribution in the major water masses of the region. The CFC-12 data are used to reconstruct the time-history of the tracer’s saturation at the time of convection based on multiple regression with the atmospheric input function of CFC-12 and the annual maximum mixed layer depth. The so-modelled time-varying saturation is employed to relax the constant saturation assumption of the Transit Time Distribution (TTD) method, allowing for a better estimate of anthropogenic carbon (Cant) in the region. We present the column inventories and storage rate of Cant in central Labrador Sea between 1986 and 2016 obtained using the TTD method with time-varying saturation. We compare these estimates with a classical TTD approach that assumes constant saturation, and we highlight the differences in trends and magnitudes obtained with the two approaches. Finally, our work shows the multi-decadal dataset of DIC in the Labrador Sea which enables a comparison between the TTD-based Cant estimates and the measured DIC trends, providing insights into temporal variability of natural carbon in the region.

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)0.000
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 score0.907
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.214
Teacher spread0.195 · 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
Published2020
Admission routes2
Has abstractyes

Explore more

Same topicMarine and coastal ecosystems→French-language works237,207→