An ARDL Analysis Of The Exchange Rates Principal Determinants: ASEAN-5 Aligned with The Yen
Bibliographic record
Abstract
People age at different rates. We have proposed that rates of aging can be quantified by the rate at which individuals accumulate health deficits. Earlier estimates, using cross-sectional analyses suggested that deficits accumulated exponentially, at an annual rate of 3.5%. Here, we estimate the rate of deficit accumulation using longitudinal data from the Canadian National Population Health Survey. By analyzing age-specific trajectories of deficit accumulation in people aged 20 years and over (n = 13,668) followed biannually for 16 years, we found that the longitudinal average annual rate of deficit accumulation was 4.5% (±0.75%). This estimate was notably stable during the adult life span. The corresponding average doubling time in the number of deficits was 15.4 (95% CI 14.82-16.03) years, roughly 30% less than we had reported from the cross-sectional analysis. Earlier work also established that the average number of deficits accumulated by individuals (N), equals the product of the intensity of environmental stresses (λ) causing damage to the organism, by the average recovery time (W). At the individual level, changes in deficit accumulation can be attributed to both changes in environmental stresses and changes in recovery time. By contrast, at the population level, changes in the number of deficits are proportional to the changes in recovery time. In consequence, we propose here that the average recovery time, W doubles approximately every 15.4 years, independently of age. Such changes quantify the increase of vulnerability to stressors as people age that gives rise to increasing risk of frailty, disability and death. That deficit accumulation will, on average, double twice between ages 50 and 80 highlights the importance of health in middle age on late life outcomes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".