MétaCan
Menu
← Back to cohort
Record W2044718654 · doi:10.1139/f04-021

Definitive identification of fatty acid constituents in marine mammal tissues

2004· article· en· W2044718654 on OpenAlexvenueno aff
Dana L. Wetzel, J. E. Reynolds

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Marine Fisheries Service
KeywordsBlubberDerivatizationGas chromatographyChemistryChromatographyFatty acidGas chromatography–mass spectrometryMass spectrometryBiochemistryBiologyFishery

Abstract

fetched live from OpenAlex

Analyses of fatty acid constituents in a sample of bowhead whale (Balaena mysticetus) blubber were conducted using a method that has not been applied before to studies of lipids in marine mammals. It involves creation and analysis of nitrogen (picolinyl) ester derivatives of the fatty acids followed by combined gas chromatography – mass spectrometry for verification of structures. Use of this approach allowed the structural confirmation of 45 different fatty acids in the blubber sample. The traditional method of methyl ester derivatization of fatty acids followed by gas chromatography – mass spectrometry analyses provides more component characterization than analyses by gas chromatography – flame ionization detection, but not enough to effectively differentiate double bond isomers or branched compounds. Although the novel approach is time intensive, we recommend that it be employed for studies where the precise identification and confirmation of fatty acids is important.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.232
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicMarine animal studies overview→French-language works237,207→