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Record W2282417939 · doi:10.1002/2015jc011232

The future of the subsurface chlorophyll‐a maximum in the <scp>C</scp>anada <scp>B</scp>asin—A model intercomparison

2015· article· en· W2282417939 on OpenAlexafffundabout
Nadja Steiner, Tessa Sou, Clara Deal, Jennifer M. Jackson, Meibing Jin, Ekaterina Popova, William J. Williams, Andrew Yool

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsASL Environmental Sciences (Canada)Environment and Climate Change CanadaFisheries and Oceans Canada
FundersEnvironment CanadaFisheries and Oceans CanadaHakai InstituteNatural Environment Research CouncilSight Research UK
KeywordsStratification (seeds)ArcticEnvironmental scienceSea iceNitrateEcosystemClimatologyAtmospheric sciencesOceanographyGeologyChemistryEcology

Abstract

fetched live from OpenAlex

Abstract Six Earth system models and three ocean‐ice‐ecosystem models are analyzed to evaluate magnitude and depth of the subsurface Chl‐ a maximum (SCM) in the Canada Basin and ratio of surface to subsurface Chl‐ a in a future climate scenario. Differences in simulated Chl‐a are caused by large intermodel differences in available nitrate in the Arctic Ocean and to some extent by ecosystem complexity. Most models reproduce the observed SCM and nitracline deepening and indicate a continued deepening in the future until the models reach a new state with seasonal ice‐free waters. Models not representing a SCM show either too much nitrate and hence no surface limitation or too little nitrate with limited surface growth only. The models suggest that suppression of the nitracline and deepening of the SCM are caused by enhanced stratification, likely driven by enhanced Ekman convergence and freshwater contributions with primarily large‐scale atmospheric driving mechanisms. The simulated ratio of near‐surface Chl‐ a to depth‐integrated Chl‐ a is slightly decreasing in most areas of the Arctic Ocean due to enhanced contributions of subsurface Chl‐ a . Exceptions are some shelf areas and regions where the continued ice thinning leaves winter ice too thin to provide a barrier to momentum fluxes, allowing winter mixing to break up the strong stratification. Results confirm that algorithms determining vertically integrated Chl‐ a from surface Chl‐ a need to be tuned to Arctic conditions, but likely require little or no adjustments in the future.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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 science0.0020.000
Research integrity0.0000.002
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 head0.036
GPT teacher head0.286
Teacher spread0.249 · 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
Published2015
Admission routes3
Has abstractyes

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