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Record W2755282582 · doi:10.1002/2017jg003881

Late Spring Nitrate Distributions Beneath the Ice‐Covered Northeastern Chukchi Shelf

2017· article· en· W2755282582 on OpenAlexaboutno aff
Kevin R. Arrigo, Matthew M. Mills, Gert L. van Dijken, Kate E. Lowry, Robert S. Pickart, Reiner Schlitzer

Bibliographic record

VenueJournal of Geophysical Research Biogeosciences · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersOffice of Polar ProgramsNational Science Foundation
KeywordsOceanographyHaloclineEnvironmental scienceWater columnSea iceMelt pondHydrographyNitrateSpring (device)SalinityArctic ice packGeologyAntarctic sea iceChemistry

Abstract

fetched live from OpenAlex

Abstract Measurements of late springtime nutrient concentrations in Arctic waters are relatively rare due to the extensive sea ice cover that makes sampling difficult. During the SUBICE (Study of Under‐ice Blooms In the Chukchi Ecosystem) cruise in May–June 2014, an extensive survey of hydrography and prebloom concentrations of inorganic macronutrients, oxygen, particulate organic carbon and nitrogen, and chlorophyll a was conducted in the northeastern Chukchi Sea. Cold (<−1.5°C) winter water was prevalent throughout the study area, and the water column was weakly stratified. Nitrate (NO 3 − ) concentration averaged 12.6 ± 1.92 μ M in surface waters and 14.0 ± 1.91 μ M near the bottom and was significantly correlated with salinity. The highest NO 3 − concentrations were associated with winter water within the Central Channel flow path. NO 3 − concentrations were much reduced near the northern shelf break within the upper halocline waters of the Canada Basin and along the eastern side of the shelf near the Alaskan coast. Net community production (NCP), estimated as the difference in depth‐integrated NO 3 − content between spring (this study) and summer (historical), varied from 28 to 38 g C m −2 a −1 . This is much lower than previous NCP estimates that used NO 3 − concentrations from the southeastern Bering Sea as a baseline. These results demonstrate the importance of using profiles of NO 3 − measured as close to the beginning of the spring bloom as possible when estimating local NCP. They also show that once the snow melts in spring, increased light transmission through the sea ice to the waters below the ice could fuel large phytoplankton blooms over a much wider area than previously known.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.043
GPT teacher head0.307
Teacher spread0.264 · 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.

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

Citations44
Published2017
Admission routes1
Has abstractyes

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