Bibliographic record
Abstract
The “Baby Boomers ” are popularly defined as persons who were born between the years 1946 and 1964. According to the California Department of Finance (CDOF), there were 9.2 million Californians (27.1 percent of the total population) who were born between 1946-1964 and were between the ages of 35-53 years in the year 1999 (Table 1a).1 Population projections indicate that by the year 2050 the Baby Boomer cohort will have declined to only three percent of the California population.2 Abridged life table data for California show that Baby Boomers age 55 in 2001 would have a total life expectancy (LE) of 27.2 years and a healthy life expectancy (HLE) of 19.9 years (Table 1b).3 Female Baby Boomers were expected to have an average of 3.2 more years of LE than their male counterparts at age 55 and 1.9 years more of HLE. A previous report on trends in deaths and death rates for California’s Baby Boomer population during the 1980’s indicated that the leading causes of death were unintentional injuries, homicide, and suicide.4 As this population ages, an epidemiologic transition from intentional and unintentional injuries to chronic diseases as leading causes of death can be anticipated. This shift will lead to additional challenges for public health and the private healthcare system during the first quarter of the new millennium, given the sheer volume the Baby Boomer population represents and their emerging healthcare needs. This report examines mortality trends for Baby Boomers during the decade of the 1990’s, and presents key findings on leading causes of death by gender and by race/ethnicity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.381 | 0.168 |
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".