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Inflammation and the Aging Process: Devil or Angel

2008· review· en· W1995402656 on OpenAlexaff
Jack Gauldie

Bibliographic record

VenueNutrition Reviews · 2008
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsInflammationFibrosisImmune systemMechanism (biology)ImmunologyTissue repairDiseaseInflammatory responseChronic infectionBiologyMedicineNeurosciencePathologyCell biology

Abstract

fetched live from OpenAlex

Inflammation is often viewed as a pathologic mechanism leading to tissue damage and interference with function, such as the process of chronic tissue scarring or fibrosis. However, it is important to note that inflammation is a crucial component of normal tissue repair as well as being fundamental to the body's defense against infection. Considering inflammation as a "causative agent in aging" belies the underlying mechanisms whereby the acute inflammatory response is necessary for survival, and efforts to reduce and control the inflammatory response leave the host susceptible to infectious agents and improper healing. Chronic inflammation inevitably has initiating mechanisms that include immune, autoimmune, and metabolic pathways, leading to the activation and presence of the host-protective response. It is more appropriate to target the underlying initiating conditions than the inflammatory process that ensues and treat the basic mechanisms of disease rather than interfere in a very important protective mechanism of the host.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.003

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.

Opus teacher head0.065
GPT teacher head0.359
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations10
Published2008
Admission routes1
Has abstractyes

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