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Record W2130395454 · doi:10.14430/arctic25

Carbon Uptake Rates of Sea Ice Algae and Phytoplankton under Different Light Intensities in a Landfast Sea Ice Zone, Barrow, Alaska

2009· article· en· W2130395454 on OpenAlexvenueno aff
Sang Heon Lee, Terry E. Whitledge, Sung‐Ho Kang

Bibliographic record

VenueARCTIC · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNOAA Ocean ExplorationNational Oceanic and Atmospheric AdministrationKorea Polar Research Institute
KeywordsAlgaePhytoplanktonSea iceOceanographyEnvironmental scienceArctic ice packNutrientGeologyEcologyBiology

Abstract

fetched live from OpenAlex

To determine whether nitrogen or light exerts the most control for the rates of carbon production of ice algae and phytoplankton under the ice, nitrogen addition (NO3 or NH4) and light increment experiments were executed on the landfast sea ice of Barrow, Alaska, during the 2003 growing season by using a 13C-15N dual isotope tracer technique. The productivity of the bottom sea ice algae and phytoplankton at Barrow in 2003 was limited mainly by low light levels (approximately 0.3% of the surface irradiance) at the bottom under the snow-covered sea ice. The carbon and nitrate uptake rates of ice algae and phytoplankton increased as the incubation depth in the ice hole decreased and light intensity increased. In addition, under higher light conditions, the relative production of proteins of the bottom ice algae decreased, whereas the lipid proportion increased. The higher level of lipid synthesis of the ice algae might be significant to the nutrition of zooplankton and benthos because lipids are the most energy-dense biomolecules.

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)0.000
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 score0.018
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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

Citations31
Published2009
Admission routes1
Has abstractyes

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Same venueARCTICSame topicArctic and Antarctic ice dynamicsFrench-language works237,207