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Record W4410550118 · doi:10.1128/cmr.00005-20

Practical Guidance for Clinical Microbiology Laboratories: Antibody and antigen detection methods for dimorphic fungal infections

2025· review· en· W4410550118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Microbiology Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersMayo Clinic
KeywordsCoccidioidesDimorphic fungusCoccidioides immitisBlastomyces dermatitidisSerologyAntigenBiologyMicrobiologyBlastomycosisBlastomycesAntibodyImmunologyVirologyYeast

Abstract

fetched live from OpenAlex

SUMMARY Antibody and antigen detection assays continue to play a significant role in the diagnosis of dimorphic fungal pathogens, including Blastomyces dermatitidis complex, Coccidioides immitis/posadasii , Paracoccidioides species, Histoplasma species , Sporothrix species, and Talaromyces marneffei . The performance characteristics of serologic and antigen detection assays for these pathogens are variable, however, influenced by multiple factors, including sample type, disease presentation, patient immunostatus, and timing of specimen collection relative to symptom onset. As a result, there is a need for a centralized document summarizing the accuracy of currently available antibody and antigen detection assays for each of these agents, including discussion of individual assay nuances and caveats that should be considered by clinicians and laboratorians alike. In addition, this review provides expert recommendations for the utilization and interpretation of serologic and antigen detection assays for these dimorphic pathogens.

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.

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)0.010
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.934
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.002
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 head0.284
GPT teacher head0.614
Teacher spread0.330 · 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