Bibliographic record
Abstract
Inflammation may be defined as the normal response of living tissue to injury or infection. It is important to emphasize two components of this definition. First, that inflammation is a normal response and, as such, is expected to occur when tissue is damaged. Indeed, if injured tissue did not exhibit signs of inflammation this would be considered abnormal. Secondly, inflammation occurs in living tissue, hence the need for an adequate blood supply to the tissues in order for an inflammatory response to be exhibited. The inflammatory response may be triggered by mechanical injury, chemical toxins, invasion by microorganisms, and hypersensitivity reactions. Three major events occur during the inflammatory response: the blood supply to the affected area is increased substantially, capillary permeability is increased, and leucocytes migrate from the capillary vessels into the surrounding interstitial spaces to the site of inflammation or injury. The inflammatory response represents a complex biological and biochemical process involving cells of the immune system and a plethora of biological mediators. Cell-to-cell communication molecules known collectively as cytokines play an extremely important role in mediating the process of inflammation. An extensive exposition of this complex phenomenon is beyond the scope of this article. Rather, the author provides a review of inflammation, an overview of the role of certain biological mediators in inflammation, and a discussion of the implications of certain biological response modifiers in clinical practice.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".