Bibliographic record
Abstract
Few disorders have as broad implications for public health and cardiovascular medicine as myocardial infarction. Herrick’s first description in living man in 1912 was populated by a combination of clinical symptoms and electrocardiographic changes.1 In this prescient description of six cases, the diagnosis was confirmed at autopsy in one who died 3 days after his clinical diagnosis. Interestingly, a period of relative quiescence ensued after Herrick’s original description. In 1959, the World Health Organization contributed to the definition of myocardial infarction with the admonition that it consist of a combination of two of the following three characteristics2: Subsequently, major interest and animated debate emerged concerning the frequency, causes, preferred treatment, and prognosis of acute myocardial infarction. A convergence of factors, including those listed in box 1, helped to galvanise interest in better defining myocardial infarction with a view to both greater sensitivity and specificity. #### Box 1 Factors stimulating better definition of myocardial infarction Given this global significance of myocardial infarction and these multifactorial factors, it was decided that the European Society of Cardiology and American College of Cardiology should convene a consensus conference in July 1999 to examine potential new definitions of myocardial infarction.3 The International Task Force set upon its work recognising that any change in the definition of such an important diagnostic entity might have profound and different implications depending on a particular interest of the individual or group. Figure 1 summarises some of the stakeholders and constituencies so affected. Figure 1 Summary of key stakeholders interested in the definition of myocardial infarction. The key elements of the 2000 consensus document emerging …
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".