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Biological Mediators of Acute Inflammation

2004· review· en· W1980313380 on OpenAlexaff
James A. Rankin

Bibliographic record

VenueAACN Clinical Issues Advanced Practice in Acute & Critical Care · 2004
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInflammationImmune systemImmunologyMedicineBiology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.508
Teacher spread0.430 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations212
Published2004
Admission routes1
Has abstractyes

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