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Record W4417286415 · doi:10.1038/s41586-025-09780-8

Author Correction: Unravelling cysteine-deficiency-associated rapid weight loss

2025· erratum· en· W4417286415 on OpenAlexaff
Alan Varghese, Ivan Gusarov, Begoña Gamallo-Lana, Daria Dolgonos, Yatin Mankan, Ilya Shamovsky, Mydia Phan, Rebecca Jones, Maria Gomez-Jenkins, Eileen White, Rui Wang, Drew R. Jones, Thales Papagiannakopoulos, Michael E. Pacold, Adam C. Mar, Dan R. Littman, Evgeny Nudler

Bibliographic record

VenueNature · 2025
Typeerratum
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsYork University
Fundersnot available
KeywordsWeight lossBody weight

Abstract

fetched live from OpenAlex

In the version of the article initially published, there was a copy-paste error in Extended Data Fig. 2f,g. Specifically, the muscle H&E panel for Day 3 Het No Cys was identical to the Day 7 KO Ctrl diet, and the Day 3 KO Ctrl panel was identical to the Day 7 KO No Cys. These errors involved the incorrect panels for Day 3 Het No Cys and Day 3 KO Ctrl. The figure has now been updated with the correct panels in both the HTML and PDF versions of the article. This error did not affect the conclusions of the figure or the overall paper.

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)0.028
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0320.015

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 head0.013
GPT teacher head0.309
Teacher spread0.296 · 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
GenreOther

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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