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Record W2900536852 · doi:10.18632/aging.101646

Aging and drug discovery

2018· article· en· W2900536852 on OpenAlex
Daniela Bakula, Alexander Aliper, Polina Mamoshina, Michael Petr, Amanuel Teklu, Joseph A. Baur, Judith Campisi, Collin Y. Ewald, Anastasia Georgievskaya, Vadim N. Gladyshev, Olga Kovalchuk, Dudley W. Lamming, Martijn S. Luijsterburg, Alejandro Martín‐Montalvo, Stuart Maudsley, Garik V. Mkrtchyan, Alexey Moskalev, S. Jay Olshansky, Ivan V. Ozerov, Alexander Pickett, Michael Ristow, Alex Zhavoronkov, Morten Scheibye‐Knudsen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAging · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Lethbridge
FundersInstituto de Salud Carlos IIINovo NordiskNederlandse Organisatie voor Wetenschappelijk OnderzoekNovo Nordisk FondenFondation pour la Recherche MédicaleNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungLeids Universitair Medisch CentrumEuropean CommissionDeutsche ForschungsgemeinschaftStrongNational Institute on AgingGlenn Foundation for Medical ResearchNational Science Foundation
KeywordsTransformative learningDrug discoveryPsychological interventionLongevityProcess (computing)Successful agingEngineering ethicsPolitical scienceMedicineGerontologyPsychologyComputer scienceBiologyEngineeringBioinformatics

Abstract

fetched live from OpenAlex

Multiple interventions in the aging process have been discovered to extend the healthspan of model organisms. Both industry and academia are therefore exploring possible transformative molecules that target aging and age-associated diseases. In this overview, we summarize the presented talks and discussion points of the 5th Annual Aging and Drug Discovery Forum 2018 in Basel, Switzerland. Here academia and industry came together, to discuss the latest progress and issues in aging research. The meeting covered talks about the mechanistic cause of aging, how longevity signatures may be highly conserved, emerging biomarkers of aging, possible interventions in the aging process and the use of artificial intelligence for aging research and drug discovery. Importantly, a consensus is emerging both in industry and academia, that molecules able to intervene in the aging process may contain the potential to transform both societies and healthcare.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.230
Teacher spread0.224 · 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