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Record W2131143284 · doi:10.1139/a2012-007

Modelling the role of highly unsaturated fatty acids in planktonic food web processes: a mechanistic approach

2012· article· en· W2131143284 on OpenAlexafffundvenue
Gurbir Perhar, George B. Arhonditsis, Michael T. Brett

Bibliographic record

VenueEnvironmental Reviews · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsThe Scarborough Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZooplanktonTrophic levelFood webPlanktonBiomass (ecology)PopulationBiologyFood chainEcologyNutrientEnvironmental science

Abstract

fetched live from OpenAlex

Highly unsaturated fatty acids (HUFAs) are a subgroup of fatty acids characterized by chains of 20 or more carbon atoms with multiple double bonds, which potentially limit the growth of zooplankton. Zooplankton require high HUFA concentrations during periods of rapid growth, but co-limitation with nutrients is also likely to occur. Recent modelling results suggest food webs with high quality (nutritional and biochemical) primary producers can attain inverted biomass distributions with efficient energy transfer between trophic levels. In this study, our objective is to highlight the recent advances in studying the role of HUFAs in aquatic food webs. We take a first-principles approach to investigate the chemical nature of HUFAs, and the role they play in zooplankton ecology. To this end, we introduce a novel zooplankton growth sub model that tracks the interplay between nitrogen, phosphorus, and HUFAs in plankton population models. Our aim is to produce a sub model that incorporates the knowledge gained from decades of biochemical research into management-oriented predictive tools.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.168

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 head0.026
GPT teacher head0.203
Teacher spread0.177 · 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 designBench or experimental
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

Citations38
Published2012
Admission routes3
Has abstractyes

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