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Immunity to Fungi

2018· other· en· W2913937522 on OpenAlexaff
Christina Michalski, Manish Sadarangani, Pascal M. Lavoie

Bibliographic record

VenueEncyclopedia of Life Sciences · 2018
Typeother
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyImmune systemDiseaseImmunityAcquired immune systemInnate immune systemImmunologyHost (biology)MedicineEcology

Abstract

fetched live from OpenAlex

Abstract Fungi are microorganisms that are ubiquitous in the environment. To establish themselves in the host, they employ a broad variety of virulence strategies. Fungi are an important source of morbidity in humans. However, despite millions of species, only about a hundred cause disease, owing to a remarkable collaboration of the innate and adaptive immune systems. In individuals who have immunocompromised cellular immunity, fungi readily cause invasive disease. Our knowledge of how the immune system prevents invasive fungal disease has been greatly aided by the study of acquired or inherited immune defects. However, much remains to be known in order to improve our ability to treat fungal infections, and our ability to control endemic disease in many areas of the world remains limited, warranting more research towards immunomodulatory interventions. Key Concepts Fungi readily colonise the environment including our skin and mucosal surfaces. Invasive fungal infections largely occur in individuals with impaired immunity, although infections are endemic in many areas of the world in immunocompetent hosts. T cells and neutrophils are essential in preventing invasive fungal disease. In immunocompromised hosts, fungi frequently cause disease by direct invasion, and also indirectly (i.e. through exaggerated host immune responses). Fungal infections are a major cause of morbidity and mortality worldwide.

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: Other · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0500.011

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 head0.024
GPT teacher head0.312
Teacher spread0.288 · 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
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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