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Record W2071995871 · doi:10.1093/gerona/61.8.813

Of Mice and Monkeys: National Institute on Aging Resources Supporting the Use of Animal Models in Biogerontology Research

2006· review· en· W2071995871 on OpenAlexaff
Nancy L. Nadon

Bibliographic record

VenueThe Journals of Gerontology Series A · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsNonhuman primateMacaqueGerontologyPsychologyNeuroscienceBiologyPhysiologyMedicineEvolutionary biology

Abstract

fetched live from OpenAlex

The preponderance of our understanding of the biological changes that occur with aging has come from studies using rodents. Rodents are a valuable model for biogerontology research because of similarities to humans in the physiology and cell biology of aging. There are, however, many differences between rodents and humans, so application of findings in rodents to human aging requires the use of a model that is closer to humans at the genetic and physiological level. In aging research, the macaque has filled this need. There are many challenges associated with using nonhuman primates in aging research, not the least of which are the limited availability of aged monkeys and the cost of using them. To facilitate this research, the National Institute on Aging has developed several resources to assist investigators and promote the use of the nonhuman primate model in aging 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)0.004
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.015

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 head0.287
GPT teacher head0.422
Teacher spread0.135 · 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
GenreReview

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

Citations26
Published2006
Admission routes1
Has abstractyes

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