Psychosocial stress and cardiovascular disease
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
Mahatma Gandhi once famously said: "poverty is the worst type of violence". He was referring to the state of political and social unrest that was pervading his nation, and the impact that humiliating defeat had on those who suffered in dire straits. Today, there is mounting evidence that social disparities cause intense psychosocial stress on those on whom they are imposed and can result in adverse cardiovascular outcomes. In modern society we still witness large disparities in living conditions between races, regions, continents and nations. Even in more privileged nations, we often witness the existence of "food and social deserts" in the middle of large urban centers. Sizable segments of the population are deprived of the comforts and privileges enjoyed by others; food quality and choices are limited, opportunities to exercise and play are scarce or unsafe, physical and verbal violence are prevalent, and racially driven conflicts are frequent. It has become apparent that these conditions predispose to the development of cardiovascular disease and affect its outcome negatively. Besides the increase in incidence of traditional risk factors, such as smoking, hypertension, insulin resistance and obesity, several other pathophysiological mechanisms involving the neuro-endocrine, inflammatory and immune pathways may be responsible for the noted negative outcomes. In this manuscript we review some of the evidence linking social distress with adverse cardiovascular outcomes and the potential subtending mechanisms and therapeutic interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.006 | 0.004 |
| 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 | 0.001 |
| 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