Bibliographic record
Abstract
Ischemic heart disease is the leading cause of death in both developed and developing countries worldwide. There is marked regional variation across Europe in mortality rates for CHD with higher rates in the north-east and lower rates in the south-west.1 Greece seems to go against this gradient. Some developed countries have had a steady decrease in the age standardized mortality rate for CHD over the last 25–30 years. In Canada and the United States as an example, CHD mortality has fallen about 25% but remains the most common cause of death.2 However, for many developing countries with low to middle incomes there has been a steady rise in CHD incidence. This rise has been attributed to a variety of factors such as urbanization, socioeconomic and lifestyle changes.3 Common risk factors for coronary heart disease (CHD) were identified many years ago and have been studied in many countries throughout the world as contributors to the development of cardiovascular disease.4,5 There are four conventional factors: tobacco smoking, hypertension, hypercholesterolemia and diabetes and at least one of these risk factors may be found in over 80% of people with CHD.6 However, other important risk factors such as Apo B/Apo A1 ratio, abdominal obesity (waist to hip ratio), and psychosocial stress have been identified. As well protective factors have also been recognized. The InterHeart study (2004) identified that diet high in vegetables and fruits, exercise and moderate alcohol intake were found to decrease risk.3
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".