Bibliographic record
Abstract
Two of this century's most significant public health challenges are climate change and healthy aging. The future of humanity will be both warmer and older than it is today. Is it socially responsible, in a warming planet of a population exceeding 8 billion people, for science to aspire to develop gerotherapeutic drugs that aim to reduce the burden of aging-related diseases that may also increase lifespan? This question is the "elephant in the room" for geroscience advocacy. Science communication concerning what constitutes empirically valid and morally defensible ways of navigating the dual public health predicaments of climate change and healthy aging must be sensitive to both the interdependence of the environment (including planetary health) and the mechanisms of aging, as well as the common (mis)perceptions about the potential conflict between the goals of climate science and geroscience. Geroscience advocacy can transcend narratives of intergenerational conflict by highlighting the shared aspirations of climate science and geroscience, such as the goals of promoting health across the lifespan, redressing health disparities, and improving the economic prospects of current and future generations.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".