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Record W2002315403 · doi:10.5194/bg-9-925-2012

Tracing the transport of colored dissolved organic matter in water masses of the Southern Beaufort Sea: relationship with hydrographic characteristics

2011· article· en· W2002315403 on OpenAlexaff
A. Matsuoka, Annick Bricaud, Ronald Benner, J. Para, Richard Sempéré, L. Prieur, Simon Bélanger, Marcel Babin

Bibliographic record

VenueBiogeosciences · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à RimouskiTakuvik Joint International LaboratoryUniversité Laval
FundersCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesNational Science Foundation
KeywordsHydrographyBeaufort seaOceanographyColored dissolved organic matterWater massDissolved organic carbonTracingEnvironmental scienceColoredGeographyGeologyEcologySea iceBiologyPhytoplanktonComputer science

Abstract

fetched live from OpenAlex

Abstract. Light absorption by colored dissolved organic matter (CDOM) (aCDOM(λ)) plays an important role in the heat budget of the Arctic Ocean, contributing to the recent decline in sea ice, as well as in biogeochemical processes. We investigated aCDOM(λ) in the Southern Beaufort Sea where a significant amount of CDOM is delivered by the Mackenzie River. In the surface layer, aCDOM(440) showed a strong and negative correlation with salinity, indicating strong river influence and conservative transport in the river plume. Below the mixed layer, a weak but positive correlation between aCDOM(440) and salinity was observed above the upper halocline, resulting from the effect of removal of CDOM due to brine rejection and lateral intrusion of Pacific summer waters into these layers. In contrast, the relationship was negative in the upper and the lower haloclines, suggesting these waters originated from Arctic coastal waters. DOC concentrations in the surface layer were strongly correlated with aCDOM(440) (r2= 0.97), suggesting that this value can be estimated in this area, using aCDOM(440) that is retrieved using satellite ocean color data. Implications for estimation of DOC concentrations in surface waters using ocean color remote sensing are discussed.

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 score0.193
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.169
Teacher spread0.153 · 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

Citations118
Published2011
Admission routes1
Has abstractyes

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