Bibliographic record
Abstract
This chapter discusses five surveys that gather information on multiple health-related topics. The National Health Examination Surveys (NHES) and its continuation, the National Health and Nutrition Examination Survey (NHANES), have been conducted periodically since 1960 and collect data on a wide variety of health topics through personal interview and direct physical examination. The National Health Interview Survey (NHIS) has been conducted annually since 1957 and gathers information through personal interviews with members of a representative sample of American households. The Joint Canada/United States Survey of Health (JCUSH) was conducted in 2002 to 2003, with a random sample of adults age 18 and older in Canada and the United States, was the first survey to collect comprehensive information about health and health care access in both countries. The Longitudinal Studies of Aging (LSOAs) consist of four surveys designed to study longitudinal changes in the health, functional status, living arrangements, and health services of older Americans as they age; the LSOAs were begun in 1984, and data were most recently collected in 2000. The State and Local Area Integrated Telephone Survey (SLAITS) is a data collection mechanism that has been used to conduct a number of different health-related surveys at the national, state, and local levels since 1997. The National Health Examination Survey and the National Health and Nutrition Examination Survey The NHES and the NHANES form part of an ongoing effort to collect data on illness and disability in the United States.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.111 | 0.034 |
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".