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Record W2946391649 · doi:10.1029/2019gl083167

Algal Export in the Arctic Ocean in Times of Global Warming

2019· article· en· W2946391649 on OpenAlexafffund
Catherine Lalande, Eva‐Maria Nöthig, Louis Fortier

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité Laval
FundersArcticNet
KeywordsArcticEnvironmental scienceSea iceSnowmeltOceanographyCarbon cycleArctic ice packClimatologyGlobal warmingArctic sea ice declineProductivityAlgaeAntarctic sea iceClimate changeSnowGeologyEcologyEcosystemBiology

Abstract

fetched live from OpenAlex

Abstract Satellite‐derived data suggest an increase in annual primary production following the loss of summer sea ice in the Arctic Ocean. The scarcity of field data to corroborate this enhanced algal production incited a collaborative project combining six annual cycles of sequential sediment trap measurements obtained over a 17‐year period in the Eurasian Arctic Ocean. Here we present microalgal fluxes measured at ~200 m to reflect the bulk of algal carbon production. Ice algae contributed to a large proportion of the microalgal carbon export before complete ice melt and possible detection of their production by satellites. In the northern Laptev Sea, annual microalgal carbon fluxes were lower during the 2007 minimum ice extent than in 2006. In 2012, early snowmelt led to early microalgal carbon flux in the Nansen Basin. Hence, a change in the timing of snowmelt and ice algae release may affect productivity and export over the Arctic basins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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 teacher head, 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

Citations72
Published2019
Admission routes2
Has abstractyes

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