Is human aging still mysterious enough to be left only to scientists?
Bibliographic record
Abstract
The feasibility of reversing human aging within a matter of decades has traditionally been dismissed by all professional biogerontologists, on the grounds that not only is aging still poorly understood, but also many of those aspects that we do understand are not reversible by any current or foreseeable therapeutic regimen. This broad consensus has recently been challenged by the publication, by five respected experimentalists in diverse subfields of biogerontology together with three of the present authors, of an article (Ann NY Acad Sci 959, 452-462) whose conclusion was that all the key components of mammalian aging are indeed amenable to substantial reversal (not merely retardation) in mice, with technology that has a reasonable prospect of being developed within about a decade. Translation of that panel of interventions to humans who are already alive, within a few decades thereafter, was deemed potentially feasible (though it was not claimed to be likely). If the prospect of controlling human aging within the foreseeable future cannot be categorically rejected, then it becomes a matter of personal significance to most people presently alive. Consequently, we suggest that serious public debate on this subject is now warranted, and we survey here several of the biological, social and political issues relating to it.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".