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Record W2914378285 · doi:10.1029/2018gb005997

The Intraseasonal Dynamics of the Mixed Layer Pump in the Subpolar North Atlantic Ocean: A Biogeochemical‐Argo Float Approach

2019· article· en· W2914378285 on OpenAlexaff
Léo Lacour, Nathan Briggs, Hervé Claustre, Mathieu Ardyna, Giorgio Dall’Olmo

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité Laval
FundersEuropean Research CouncilHorizon 2020 Framework ProgrammeNatural Environment Research CouncilSight Research UK
KeywordsMixed layerMesopelagic zoneSpring bloomEnvironmental scienceArgoBloomOceanographyBiological pumpBiogeochemical cyclePhytoplanktonClimatologyPelagic zoneGeologyNutrientEcologyBiology

Abstract

fetched live from OpenAlex

Abstract The detrainment of organic matter from the mixed layer, a process known as the mixed layer pump (ML pump), has long been overlooked in carbon export budgets. Recently, the ML pump has been investigated at seasonal scale and appeared to contribute significantly to particulate organic carbon export to the mesopelagic zone, especially at high latitudes where seasonal variations of the mixed layer depth are large. However, the dynamics of the ML pump at intraseasonal scales remains poorly known, mainly because the lack of observational tools suited to studying such dynamics. In the present study, using a dense network of autonomous profiling floats equipped with bio‐optical sensors, we captured widespread episodic ML pump‐driven export events, during the winter and early spring period, in a large part of the subpolar North Atlantic Ocean. The intraseasonal dynamics of the ML pump exports fresh organic material to depth (basin‐scale average up to 55 mg C·m −2 ·day −1 ), providing a significant source of energy to the mesopelagic food web before the spring bloom period. This mechanism may sustain the seasonal development of overwintering organisms such as copepods with potential impact on the characteristics of the forthcoming spring phytoplankton bloom through predator‐prey interactions.

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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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

Citations93
Published2019
Admission routes1
Has abstractyes

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