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Record W4385278070 · doi:10.1002/lol2.10347

Physical controls and ecological implications of the timing of the spring phytoplankton bloom on the Newfoundland and Labrador shelf

2023· article· en· W4385278070 on OpenAlexaffabout
Frédéric Cyr, Keith P. Lewis, David Bélanger, Paul M. Regular, Stephanie Clay, Emmanuel Devred

Bibliographic record

VenueLimnology and Oceanography Letters · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersNational Aeronautics and Space Administration
KeywordsSpring bloomCalanus finmarchicusBloomZooplanktonPhytoplanktonOceanographyTrophic levelEcosystemAlgal bloomMarine ecosystemEnvironmental scienceAbundance (ecology)Food webClimate changeEcologyProductivityCalanusSpring (device)BiologyNutrientCrustaceanCopepodGeology

Abstract

fetched live from OpenAlex

Abstract The timing of spring phytoplankton blooms is crucial to many species that have adapted their development to benefit from the enhanced feeding opportunity they offer. Any change to their timing may affect the productivity of an entire ecosystem. This study explores the relationship between the ocean climate, the timing of the spring bloom and the secondary production on the Newfoundland and Labrador shelf. It is found that over interannual cycles, the ocean climate is significantly correlated with the timing of the bloom and the abundance of Calanus finmarchicus , a key zooplankton species for the ecosystem. It also appears that the spring bloom is initiated by the onset of ocean re‐stratification following winter mixing. Understanding how annual variation in climate relates to the timing of the spring bloom and zooplankton abundance, that is, the base of the marine food web, can inform the development of ecosystem‐informed models for higher trophic levels.

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 score0.021
Threshold uncertainty score0.463

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 studies0.0000.001
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 head0.013
GPT teacher head0.225
Teacher spread0.211 · 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

Citations19
Published2023
Admission routes2
Has abstractyes

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