Resolution of in flammation: state of the art, definitions and terms
Bibliographic record
Abstract
ABSTRACT A recent focus meeting on Controlling Acute Inflammation was held in London, April 27–28, 2006, organized by D.W. Gilroy and S.D. Brain for the British Pharmacology Society. We concluded at the meeting that a consensus report was needed that addresses the rapid progress in this emerging field and details how the specific study of resolution of acute inflammation provides leads for novel anti‐inflammatory therapeutics, as well as defines the terms and key components of interest in the resolution process within tissues as appreciated today. The inflammatory response protects the body against infection and injury but can itself become dysregulated with deleterious consequences to the host. It is now evident that endogenous biochemical pathways activated during defense reactions can counter‐regulate inflammation and promote resolution. Hence, resolution is an active rather than a passive process, as once believed, which now promises novel approaches for the treatment of inflammation‐associated diseases based on endogenous agonists of resolution.—Serhan, C. N., Brain, S. D., Buckley, C. D., Gilroy, D. W., Haslett, C., O'Neill, L. A. J., Perretti, M., Rossi, A. G., Wallace, J. L. Resolution of inflammation: state of the art, definitions and terms. FASEB J. 21, 325–332 (2007)
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".