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Record W2002212759 · doi:10.1093/gerona/63.4.331

The Biological Sciences Section Program at the 60th Annual Meeting of The Gerontological Society of America

2008· article· en· W2002212759 on OpenAlexaff
Rita B. Effros, Steven N. Austad, Helen M. Blau, Marie‐Françoise Chesselet, Donald K. Ingram, Thomas E. Johnson, Matt Kaeberlein, Victoria Lundblad, Roger McCarter, Janet E. McElhaney, Michael S Saag

Bibliographic record

VenueThe Journals of Gerontology Series A · 2008
Typearticle
Languageen
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsUniversity of British Columbia
FundersNational Institute on AgingEllison Medical Foundation
KeywordsTelomeraseGerontologyEpigeneticsDiseaseThe RenaissanceSuccessful agingBiologyMedicineGeneticsHistoryPathology

Abstract

fetched live from OpenAlex

In this era of genomics and other exciting technical advances, research on the biology of aging is undergoing a renaissance. This report summarizes 10 cutting-edge areas of research covered in symposia that spanned such topics as stem cells, novel vaccine strategies, nutritional sensing, new concepts of Parkinson's disease, high throughput screening for aging interventions, manipulating telomerase in cancer and immunodeficiency, synergy between aging and HIV disease, and epigenetic influences on aging. Novel animal models, including those showing no evidence of aging, as well as ethical and political implications of embryonic stem cells and alternative medicine are also discussed.

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)0.002
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.117
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.1170.054

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 head0.103
GPT teacher head0.373
Teacher spread0.269 · 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
GenreEditorial

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
Published2008
Admission routes1
Has abstractyes

Explore more

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