The Early Origins of Cardiovascular Health and Disease: Who, When, and How
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
Almost 30 years ago, a series of epidemiological studies popularized the early programming theory that had resulted from observed associations between low birthweight and increased cardiovascular morbidity and mortality later in life. Since then, several clinical and experimental models have been created to understand the principles and mechanisms of this fascinating phenomenon and describe its relevance to the pathophysiology of cardiovascular and many other chronic diseases. Despite the growing body of published evidence, the specific mechanisms mediating early programming effects are still elusive. Moreover, many controversial issues have arisen regarding the characteristics of the most commonly used clinical and experimental models, the existence of potential windows of susceptibility for different organs, and the presence of sex differences in its pathophysiology. Therefore, this review synthesizes some of the antecedents behind the early programming theory and discusses some of the controversial issues surrounding it. Early programming has been extensively linked to several chronic diseases; however, for the purposes of this review we have concentrated on the potential role of this entity in the pathophysiology of chronic cardiovascular diseases.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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