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Record W4283701282 · doi:10.1038/s42255-022-00591-z

Guidelines for measuring reactive oxygen species and oxidative damage in cells and in vivo

2022· review· en· W4283701282 on OpenAlexfundno aff
Michael P. Murphy, Hülya Bayır, Vsevolod V. Belousov, Christopher J. Chang, Kelvin J.A. Davies, Michael J. Davies, Tobias P. Dick, Toren Finkel, Henry Jay Forman, Yvonne Janssen‐Heininger, David Gems, Valerian E. Kagan, Balaraman Kalyanaraman, Nils‐Göran Larsson, Ginger L. Milne, Thomas Nyström, Henrik E. Poulsen, Rafael Radí, Holly Van Remmen, Paul T. Schumacker, Paul J. Thornalley, Shinya Toyokuni, Christine C. Winterbourn, Huiyong Yin, Barry Halliwell

Bibliographic record

VenueNature Metabolism · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRedox biology and oxidative stress
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthNational Institute on AgingUniversidad de la República UruguayNational Heart, Lung, and Blood InstituteNational Natural Science Foundation of ChinaVetenskapsrådetKnut och Alice Wallenbergs StiftelseNational Cancer InstituteNational Medical Research CouncilNational Research FoundationNational University of SingaporeNational Institute of Neurological Disorders and StrokeCanadian Institute for Advanced ResearchNational Research Foundation SingaporeMedical Research CouncilSwedish Cancer FoundationWellcome TrustNational Institute of General Medical SciencesNovo NordiskJapan Society for the Promotion of ScienceNovo Nordisk FondenPrincess Takamatsu Cancer Research FundDeutsche ForschungsgemeinschaftU.S. Department of Veterans Affairs
KeywordsReactive oxygen speciesOxidative damageOxidative phosphorylationOxidative stressIn vivoCell biologyComputational biologyChemistryBiologyBiochemistryBiotechnology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.005
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0050.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.010

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 head0.063
GPT teacher head0.352
Teacher spread0.288 · 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

Citations1,321
Published2022
Admission routes1
Has abstractno

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