Bibliographic record
Abstract
Angina pectoris is characterized by retrosternal thoracic pain, typically radiating to the left arm and triggered by physical or emotional stress or cold. It is classified according to the Canadian Cardiovascular Society into class I, II, III, or IV depending on symptom severity. Diagnosis is made clinically, with an exercise tolerance test reproducing symptoms, as well as non-invasive functional imaging, coronary CT angiography, or coronary angiography. Treatment options are anti-anginal drugs (e.g. nitrates, calcium antagonists, beta blockers, nicorandil), but angina in the context of coronary artery disease of class II or IV or persistent symptoms in spite of anti-anginal drugs is managed with percutaneous coronary intervention (PCI) and stenting or bypass surgery, respectively. Indeed, in stable anginas, anti-anginal drugs are the first choice, and if not successful, or in the presence of large ischaemic burden, PCI or bypass surgery is indicated. PCI improves symptoms of angina pectoris, but does not improve outcomes in stable coronary artery disease. Patients with left main coronary artery disease should be revascularized by either PCI or bypass surgery.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.090 | 0.052 |
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".