The intervention on aging system: A classification model, the requirement for five novel categories
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.
Bibliographic record
Abstract
Aging is widely considered an immovable fact of life. Cultural conditioning has ensured that therapeutics for extreme human lifespans are considered out of reach technologies. However, longevity therapies such as stem cell replacement, fasting, gene therapies, fasting mimetics such as metformin and rapamycin, regulation and tissue reprogramming with OSK transcription factors, blood dilution, metabolic pathway engineering, reversal of epigenetic drift, heterochronic parabiosis, coenzyme replacement technologies (nicotinamide adenine dinucleotide) and a plethora of other established sciences are showing great potential at slowing down the rate at which tissues enter dysfunction. Recent discoveries have shed light on major mysteries of the aging process. Longevity-based discoveries are not only landing quickly, but therapies to prevent or reverse those drivers of aging are also being devised regularly and this is opening up an entirely new industry, the longevity industry. This presents the requirement for a new classification system where subjects can be divided into specific groups based on their potential for mortality. This system also enables the public to target which class of this classification system they wish to be on. Moving the population on the classification system to become more disease resistant holds great benefit for society and governments as a whole.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it