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Record W2472219129 · doi:10.1002/2016jc011779

Vertical fluxes of nitrate in the seasonal nitracline of the Atlantic sector of the Arctic Ocean

2016· article· en· W2472219129 on OpenAlexaff
Achim Randelhoff, Ilker Fer, Arild Sundfjord, Jean‐Éric Tremblay, Marit Reigstad

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité Laval
FundersKlima- og miljødepartementetNorges Forskningsråd
KeywordsNitrateStratification (seeds)ArcticEnvironmental scienceOceanographySea iceArctic ice packFlux (metallurgy)Atmospheric sciencesThe arcticSeasonalityClimatologyGeologyChemistryEcologyBiology

Abstract

fetched live from OpenAlex

Abstract This study compiles colocated oceanic observations of high‐resolution vertical profiles of nitrate concentration and turbulent microstructure around the Svalbard shelf slope, covering both the permanently ice‐free Fram Strait and the pack ice north of Svalbard. The authors present an overview over the seasonal evolution of the distribution of nitrate and its relation to upper ocean stratification. The average upward turbulent diffusive nitrate flux across the seasonal nitracline during the Arctic summer season is derived, with average values of 0.3 and 0.7 mmol m −2 d −1 for stations with and without ice cover, respectively. The increase under ice‐free conditions is attributed to different patterns of stratification under sea ice versus open water. The nitrate flux obtained from microstructure measurements lacked a seasonal signal. However, bottle incubations indicate that August nitrate uptake was reduced by more than an order of magnitude relative to the May values. It remains inconclusive whether the new production was limited by an unidentified factor other than supply in late summer, or the uptake was underestimated by the incubation method.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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

Citations48
Published2016
Admission routes1
Has abstractyes

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