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Record W2607239981 · doi:10.1111/hdi.12566

Catheter‐related fungal endocarditis caused by <i>Candida parapsilosis</i> in a hemodialysis patient

2017· article· en· W2607239981 on OpenAlexvenueno aff
Ying Shu, Shaobin Yu, Ling Zha, Ping Fu, Tianlei Cui

Bibliographic record

VenueHemodialysis International · 2017
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisEndocarditisCandida parapsilosisIncidence (geometry)Hemodialysis CatheterCatheterPopulationSurgeryInfective endocarditisIntensive care medicineInternal medicineAntifungalDermatology

Abstract

fetched live from OpenAlex

Fungal endocarditis (FE) is commonly regarded as a rare but fatal disease. The incidence of infective endocarditis (IE) in hemodialysis (HD) patients is thought to be obviously higher than that in the general population. Moreover, IE occurs more likely in HD patients with catheters. With the increase of HD population and extensive use of catheters in HD patients, FE, as a special form of IE, may increase and bring new challenges to clinicians. We reported a case of FE associated with catheter infection in a 44-year-old woman on HD. The risk factors and treatment strategies of FE in HD patients were discussed.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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