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Record W4409236056 · doi:10.1016/j.xpro.2025.103745

Protocol for dual metabolomics and proteomics using nanoflow liquid chromatography-tandem mass spectrometry

2025· article· en· W4409236056 on OpenAlexfundno aff
Weiwei Lin, Fatemeh Mousavi, Benjamin C. Blum, Christian F. Heckendorf, Matthew Lawton, Noah Lampl, Ryan Hekman, Mark E. McComb, Andrew Emili

Bibliographic record

VenueSTAR Protocols · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchBoston University
KeywordsChromatographyMetabolomicsLiquid chromatography–mass spectrometryChemistryMass spectrometryTandem mass spectrometryProteomicsProtocol (science)Dual (grammatical number)MedicineBiochemistry

Abstract

fetched live from OpenAlex

.

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)0.002
metaresearch head score (Gemma)0.002
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: Protocol · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0460.050

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 head0.337
Teacher spread0.311 · 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
GenreProtocol

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

Citations1
Published2025
Admission routes1
Has abstractyes

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