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Record W2023335257 · doi:10.1016/j.ijid.2009.05.012

Articular aspergillosis: case report and review of the literature

2009· article· en· W2023335257 on OpenAlexaff
Oriana Hoi Yun Yu, Annick Wong Wong Keet, Donald C. Sheppard, Timothy F. Brewer

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2009
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsVoriconazoleAspergillosisCaspofunginMedicineIncidence (geometry)Hematopoietic stem cell transplantationAmphotericin BDermatologyPathologyAntifungalImmunologyDisease

Abstract

fetched live from OpenAlex

The incidence of invasive aspergillosis is increasing due to more frequent use of immunosuppressant agents in patients with autoimmune diseases, hematological malignancies, and solid organ and hematopoietic stem cell transplants. Invasive aspergillosis most commonly affects the lungs, sinuses, and brain. Aspergillosis affecting the musculoskeletal system is rare. We describe here a case of articular aspergillosis in a febrile neutropenic patient successfully treated with voriconazole and caspofungin, and briefly review the 10 cases of articular aspergillosis that have previously been described in the literature.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.006
GPT teacher head0.294
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 designCase report
Domainnot available
GenreEmpirical

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

Citations20
Published2009
Admission routes1
Has abstractyes

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