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Record W2027084368 · doi:10.1089/rej.2005.8.29

Thermodynamics and Information in Aging: Why Aging Is Not a Mystery and How We Will Be Able to Make Rational Interventions

2005· article· en· W2027084368 on OpenAlex
Mark Hamalainen

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

VenueRejuvenation Research · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsContext (archaeology)Natural selectionProcess (computing)Selection (genetic algorithm)Psychological interventionComputer scienceField (mathematics)Natural (archaeology)Management scienceEpistemologyData sciencePsychologyArtificial intelligenceEconomicsBiologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Currently, the aging research field lacks consensus in its focus and methodology. Foundational principles, such as the evolutionary origins and physiological definition of aging, remain controversial. The aim of this paper is to resolve these issues. By applying the concepts of thermodynamics and information in an evolutionary context, the aging phenotype can be derived from first principles. Life uses information storage to maintain its distance from thermodynamic equilibrium. Since it is impossible to make any process 100% efficient, a selective force (i.e., natural selection) is needed to maintain the information's viability. Natural selection operates upon generations, and for reasons discussed subsequently, the somatic body cannot implement an analogous selective process. The aging phenotype we see can be derived from this model along with a number of insights that will enhance our ability to make intelligent and rational interventions.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.044
GPT teacher head0.333
Teacher spread0.289 · 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