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Record W2175076304 · doi:10.1371/journal.ppat.1005198

50 Years of Emmonsia Disease in Humans: The Dramatic Emergence of a Cluster of Novel Fungal Pathogens

2015· review· en· W2175076304 on OpenAlexaff
Ilan S. Schwartz, Chris Kenyon, Peiying Feng, Nelesh P. Govender, Karolina Dukik, Lynne Sigler, Yanping Jiang, J. Benjamin Stielow, José F. Muñoz, Christina A. Cuomo, Alfred Botha, Alberto M. Stchigel, Sybren de Hoog

Bibliographic record

VenuePLoS Pathogens · 2015
Typereview
Languageen
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsUniversity of AlbertaUniversity of Manitoba
FundersAstellas PharmaFonds Wetenschappelijk OnderzoekVlaamse regeringUniversidad de AntioquiaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsBiologyFungal diseaseMicrobiologyCluster (spacecraft)Virology

Abstract

fetched live from OpenAlex

ABSTRACT: New species of Emmonsia-like fungi, with phylogenetic and clinical similarities to Blastomyces and Histoplasma, have emerged as causes of systemic human mycoses worldwide. They differ from classical Emmonsia species by producing a thermally-dependent, yeast-like phase rather than adiaspores, and by causing disseminated infections, predominantly in immunocompromised patients and often with high case-fatality rates. Such differences will be important for clinicians to consider in diagnosis and patient management, and for microbiologists who may encounter these fungi with increasing frequency. (Tomado de la introducción del artículo)

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.126
GPT teacher head0.364
Teacher spread0.238 · 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

Citations76
Published2015
Admission routes1
Has abstractyes

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