Bibliographic record
Abstract
C-reactive protein (CRP) is a unique risk marker and plays a role in the pathogenesis of inflammation and atherosclerosis. It is synthesized and secreted mainly by hepatocytes in response to interleukin-6 (IL-6) and either IL-1 or tumor necrosis factor-alpha. The average plasma half life of CRP is 19 hours. CRP activates complement, increases phagocytic activity of neutrophils, increases respiratory burst of neutrophils, and induces expression of adhesion molecules, synthesis of tissue factor, cytokines from monocytes and platelet aggregation. CRP is involved in development of atherosclerosis and thrombosis. High sensitive-CRP (hs-CRP) is a very novel biochemical marker. It is elevated in various conditions including: inflammation both acute and chronic, acute myocardial infarction, unstable angina, peripheral vascular diseases, diabetes, renal disease, hypertension, and cardiopulmonary bypass. A positive association has been reported between CRP levels and age, smoking, body mass, total cholesterol, lipoprotein a [Lp(a)], homocysteine and fibrinogen. It has a predictive value for the development of peripheral vascular disease, restenosis following percutaneous coronary interventions with or without stent implantation, and complications following cardiopulmonary bypass. Preprocedural high levels of plasma CRP are associated with high incidence of late adverse events (composite of cardiac death, nonfatal myocardial infarction, clinical occurrence of symptoms, progression of significant coronary lesion in vessels other then treated ones) after successful coronary stenting. Baseline levels of CRP predict risk of future myocardial infarction, and stroke in apparently healthy middle-aged men and women. CRP levels predict atherosclerotic vascular disease in patients with end-stage renal disease. Increased pretransplant CRP levels are associated with higher risk of acute rejection in transplant recipients. Various strategies to reduce the adverse effects of CRP have been discussed.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".