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Record W4320075819 · doi:10.15173/sciential.vi8.3035

Stopping Aging: Dream or Reality?

2022· article· en· W4320075819 on OpenAlex
Syed Irfan

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSciential - McMaster Undergraduate Science Journal · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDreamDiseaseGerontologyProcess (computing)Diabetes mellitusMedicinePsychologyPsychological interventionIntensive care medicineNeuroscienceCognitive psychologyRisk analysis (engineering)Computer sciencePathologyPsychiatry

Abstract

fetched live from OpenAlex

Aging is a reality and is associated with the progressive physiological breakdown of the body. This can cause many health problems such as heart disease, cerebrovascular disease, diabetes, etc. However, some claim that the aging process can be stopped. Proposed mechanisms for stopping aging include good nutrition and exercise, pharmacological interventions, and stem cell therapy. These have shown good prospects for slowing down the aging process, but not for stopping it altogether. It may also not be possible to stop aging for a long time, considering that it is polygenic and complex in nature. This provides a clarification for the current state of modern science in terms of its ability to stop aging, as well as an outlook for what to expect in the future.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.001
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 head0.026
GPT teacher head0.284
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