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Record W1995754383 · doi:10.1016/j.febslet.2008.07.053

Corrigendum to “Identification of otubain 1 as a novel substrate for the <i>Yersinia</i> protein kinase using chemical genetics and mass spectrometry” [FEBS Lett. 580 (2006) 179–183]

2008· erratum· en· W1995754383 on OpenAlexafffund
Stephen Juris, Kavita Shah, Kevan M. Shokat, Jack E. Dixon, Panayiotis O. Vacratsis

Bibliographic record

VenueFEBS Letters · 2008
Typeerratum
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthFondation pour la Recherche Médicale
KeywordsIdentification (biology)Foundation (evidence)Mass spectrometryLibrary scienceComputational biologySubstrate (aquarium)Research councilChemistryBiologyPolitical sciencePhilosophyComputer scienceChromatographyBotany

Abstract

fetched live from OpenAlex

An unfortunate error was made in the Acknowledgements. It should read: This work was funded by a Natural Sciences and Engineering Research Council (NSERC) Discovery Grant 298468 (to P.O.V.), a National Institutes of Health (NIH) Grant 18849 (to J.E.D.), NIH Molecular Mechanisms of Microbial Pathogenesis Training Grant AI07528 (to S.J.J.), the Walther Cancer Institute (to J.E.D.), and the Ellison Foundation for Medical Research.

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)0.003
metaresearch head score (Gemma)0.024
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 score0.051
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.003
Science and technology studies0.0050.003
Scholarly communication0.0030.003
Open science0.0050.003
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0510.045

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 head0.027
GPT teacher head0.254
Teacher spread0.227 · 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
Published2008
Admission routes2
Has abstractyes

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