General Introduction: Amsterdam Growth and Health Longitudinal Study
Bibliographic record
Abstract
A unique observational long-term study In a long follow-up period of 23 years about 600 teenagers were observed till their young adult age in order to investigate the longitudinal relationship between health and lifestyles considering physical activity, diet, smoking and alcohol consumption. Longitudinal studies with a follow-up lasting for a quarter of a century are very rare and the Amsterdam Growth and Health Longitudinal Study (AGAHLS) is indeed unique among them. The focus is multidisciplinary and involves both physical and psychological determinants in relation to a wide range of health outcomes. The multiple measurements were carefully standardized in nine waves of data collection, thus producing a high-quality data set, which has been analyzed by the application of advanced statistical techniques. The monograph provides not only an overview of 23 years of follow-up, it also summarizes over 200 scientific publications and 10 PhD theses. This publication is especially recommended to investigators planning longitudinal research, to health workers, and to authorities who like to implement health promotional activities in their community.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 0.025 |
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".