MétaCan
Menu
Back to cohort
Record W4296736437 · doi:10.3389/fendo.2022.1037434

Corringendum: The effects of neurogranin knockdown on SERCA pump efficiency in soleus muscles of female mice fed a high fat diet

2022· erratum· en· W4296736437 on OpenAlexaff
Jessica L. Braun, Jisook Ryoo, Kyle Goodwin, Emily N. Copeland, Mia S. Geromella, Ryan W. Baranowski, Rebecca E. K. MacPherson, Val A. Fajardo

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typeerratum
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsBrock University
Fundersnot available
KeywordsGene knockdownNeurograninSERCASoleus muscleEndocrinologyInternal medicineChemistryMedicineCell biologyBiologySignal transductionBiochemistrySkeletal muscleGene

Abstract

fetched live from OpenAlex

In the published article, there was an error in the text. The source of the neurogranin mouse colony was incorrect. A correction has been made to the Methods, animals, section. This sentence previously stated:“[A breeding colony of heterozygous Ng knockout mice (Ng+/-) and wild-type (WT) mice on a 129/Sv and C57BL/6J mixed background was established at Brock University using cryorecovered breeding pairs from the Mutant Mouse Resource and Research Centre (mmRRC, stock#043288-MU).]”The corrected sentence appears below:“[A breeding colony of heterozygous Ng knockout mice (Ng+/-) and wild-type (WT) mice on a 129/Sv and C57BL/6J mixed background was established at Brock University using cryorecovered breeding pairs from the Jackson Laboratories (stock#008233).]”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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)0.010
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 score0.096
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0960.045

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in EndocrinologySame topicAdipose Tissue and MetabolismFrench-language works237,207