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Record W1983733947 · doi:10.1139/f02-062

Among- and within-species variability in fatty acid signatures of marine fish and invertebrates on the Scotian Shelf, Georges Bank, and southern Gulf of St. Lawrence

2002· article· en· W1983733947 on OpenAlexfundvenueno aff
Suzanne M. Budge, Sara J. Iverson, W. Don Bowen, R. G. Ackman

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTrophic levelInvertebrateBiologyFatty acidPredationEcology

Abstract

fetched live from OpenAlex

The fat and fatty acid compositions of 28 species of fish and invertebrates (n = 954) from the Scotian Shelf, Georges Bank, and the Gulf of St. Lawrence were determined. Discriminant analysis of the 16 most numerous species (n [Formula: see text] 18 each), using 17 major fatty acids, classified species with greater than 98% accuracy and grouped species into three general clusters (gadids, flatfish, and planktivores) with similar fatty acid compositions, and likely, similar diets. A number of species exhibited changes in fatty acid signatures with increasing size (multivariate analysis of variance), which corresponded with known dietary shifts reported from stomach contents analyses. Location effects were also observed among the three major geographical regions and were probably due to broad-scale variations in prey assemblages and phytoplankton composition in the northwestern Atlantic. Despite these effects, within-species variation was still substantially less than among-species variation. Thus, fatty acid signatures can be used to distinguish and characterize fish and invertebrate species in a given ecosystem, as well as to study finer-scale trophic interactions of these species. These data also have applications at higher trophic levels and will serve as a prey database for studying the diets of other fish and marine mammal predators using fatty acid signatures.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.196
Teacher spread0.178 · 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

Citations262
Published2002
Admission routes2
Has abstractyes

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