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Record W1969437137 · doi:10.4161/viru.25436

Host innate immune responses to sepsis

2013· review· en· W1969437137 on OpenAlexaff
W. Joost Wiersinga, Stije J. Leopold, Duncan R Cranendonk, Tom van der Poll

Bibliographic record

VenueVirulence · 2013
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsInstitute of Infection and Immunity
FundersZonMw
KeywordsBiologyImmune systemPattern recognition receptorSepsisInnate immune systemPathogenImmunologyPathogen-associated molecular patternVirulenceReceptorInflammationGeneGenetics

Abstract

fetched live from OpenAlex

The immune response to sepsis can be seen as a pattern recognition receptor-mediated dysregulation of the immune system following pathogen invasion in which a careful balance between inflammatory and anti-inflammatory responses is vital. Invasive infection triggers both pro-inflammatory and anti-inflammatory host responses, the magnitude of which depends on multiple factors, including pathogen virulence, site of infection, host genetics, and comorbidities. Toll-like receptors, the inflammasomes, and other pattern recognition receptors initiate the immune response after recognition of danger signals derived from microorganisms, so-called pathogen-associated molecular patterns or derived from the host, so-called danger-associated molecular patterns. Further dissection of the role of host-pathogen interactions, the cytokine response, the coagulation cascade, and their multidirectional interactions in sepsis should lead toward the development of new therapeutic strategies in sepsis.

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)0.000
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.189
GPT teacher head0.428
Teacher spread0.239 · 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

Citations465
Published2013
Admission routes1
Has abstractyes

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