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Record W2172276411 · doi:10.2337/db15-0386

Response to Comment on Vandal et al. Insulin Reverses the High-Fat Diet–Induced Increase in Brain Aβ and Improves Memory in an Animal Model of Alzheimer Disease. Diabetes 2014;63:4291–4301

2015· letter· en· W2172276411 on OpenAlexaff
Milène Vandal, Frédéric Calon

Bibliographic record

VenueDiabetes · 2015
Typeletter
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAnimal modelEndocrinologyInternal medicineInsulinDiabetes mellitusDiseaseType 2 diabetesMedicineInsulin responsePlasma glucose

Abstract

fetched live from OpenAlex

We thank Drs. Ghanim and Dandona for their comments (1) on our article (2). Their results showing that insulin infusion leads to decreased expression of amyloid precursor protein (APP) and presenilins in human monocytes (3) are in line with reports in cell culture (4) and support the use of insulin in Alzheimer disease (AD) (5). In triple transgenic (3xTg-AD) mice fed with a high-fat diet for 9 …

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)0.014
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0340.028
Insufficient payload (model declined to judge)0.0070.011

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 head0.034
GPT teacher head0.291
Teacher spread0.258 · 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
GenreCommentary

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

Citations3
Published2015
Admission routes1
Has abstractyes

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