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Record W7115562993 · doi:10.17863/cam.123969

Technical recommendations for analyzing oxylipins by liquid chromatography-mass spectrometry.

2025· article· en· W7115562993 on OpenAlexfundno aff

Bibliographic record

VenueApollo (University of Cambridge) · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsnot available
FundersAgency for Toxic Substances and Disease RegistryInstituto de Salud Carlos IIIMedical Research CouncilNational Institutes of HealthBundesministerium für Bildung und ForschungAgencia Estatal de InvestigaciónFundação de Amparo à Pesquisa do Estado de São PauloU.S. Department of AgricultureNatural Sciences and Engineering Research Council of CanadaEuropean CommissionAlzheimer's AssociationCentro de Estudos Ambientais e Marinhos, Universidade de AveiroWellcome TrustDeutsche ForschungsgemeinschaftCenters for Disease Control and Prevention
KeywordsLipidomicsHuman healthPathway analysisLipid signaling

Abstract

fetched live from OpenAlex

Several oxylipins are potent lipid mediators that regulate diverse aspects of health and disease and whose quantitative analysis by liquid chromatography-mass spectrometry (LC-MS) presents substantial technical challenges. As members of the lipidomics community, we developed technical recommendations to ensure best practices when quantifying oxylipins by LC-MS.

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)0.029
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.050
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.061
Meta-epidemiology (narrow)0.0070.005
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0120.004
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0060.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0500.105

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes1
Has abstractyes

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