MétaCan
Menu
Back to cohort
Record W2138103041 · doi:10.18632/aging.100132

Impact papers on aging in 2009

2010· review· en· W2138103041 on OpenAlexaff
Mikhail V. Blagosklonny, J. Campisi, David Sinclair, Andrzej Bartke, Marı́a A. Blasco, William M. Bonner, Vilhelm A. Bohr, Robert M. Brosh, Anne Brunet, Ronald A. DePinho, Lawrence A. Donehower, Caleb E. Finch, Toren Finkel, Myriam Gorospe, Andrei V. Gudkov, Michael N. Hall, Siegfried Hekimi, Stephen L. Helfand, Jan Karlseder, Cynthia Kenyon, Guido Kroemer, Valter D. Longo, André Nussenzweig, Heinz D. Osiewacz, Daniel S. Peeper, Thomas A. Rando, K. Lenhard Rudolph, Paolo Sassone‐Corsi, Manuel Serrano, Norman E. Sharpless, Vladimir P. Skulachev, Jonathan L. Tilly, John Tower, Eric Verdin, Jan Vijg

Bibliographic record

VenueAging · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsMcGill University
FundersNational Cancer InstituteNational Institute on Aging
KeywordsArt historyArtPhilosophyHumanitiesEnvironmental ethics

Abstract

fetched live from OpenAlex

The Editorial Board of Aging reviews research papers published in 2009, which they believe have or will have significant impact on aging research. Among many others, the topics include genes that accelerate aging or in contrast promote longevity in model organisms, DNA damage responses and telomeres, molecular mechanisms of life span extension by calorie restriction and pharmacological interventions into aging. The emerging message in 2009 is that aging is not random but determined by a genetically-regulated longevity network and can be decelerated both genetically and pharmacologically.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0340.029

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 head0.021
GPT teacher head0.326
Teacher spread0.305 · 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.

Study designNot applicable
DomainEvaluation
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

Citations38
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueAgingSame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207