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Record W4324360815 · doi:10.3390/pathogens12030456

Of Mycelium and Men: Inherent Human Susceptibility to Fungal Diseases

2023· review· en· W4324360815 on OpenAlexafffund
Donald C. Vinh

Bibliographic record

VenuePathogens · 2023
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsMcGill University Health Centre
FundersFonds de Recherche du Québec - Santé
KeywordsMyceliumBiologyMicrobiologyBotany

Abstract

fetched live from OpenAlex

In medical mycology, the main context of disease is iatrogenic-based disease. However, historically, and occasionally, even today, fungal diseases affect humans with no obvious risk factors, sometimes in a spectacular fashion. The field of "inborn errors of immunity" (IEI) has deduced at least some of these previously enigmatic cases; accordingly, the discovery of single-gene disorders with penetrant clinical effects and their immunologic dissection have provided a framework with which to understand some of the key pathways mediating human susceptibility to mycoses. By extension, they have also enabled the identification of naturally occurring auto-antibodies to cytokines that phenocopy such susceptibility. This review provides a comprehensive update of IEI and autoantibodies that inherently predispose humans to various fungal diseases.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.096
GPT teacher head0.397
Teacher spread0.300 · 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 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
Published2023
Admission routes2
Has abstractyes

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