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Record W2236690878 · doi:10.1155/2014/802481

Bacteremia Caused by <i>Eggerthella lenta</i> in an Elderly Man with a Gastrointestinal Malignancy: A Case Report

2014· article· en· W2236690878 on OpenAlexaff
Davie Wong, Fred Y. Aoki, Ethan Rubinstein

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBacteremiaMalignancyMedicineInternal medicineMicrobiologyBiology

Abstract

fetched live from OpenAlex

Eggerthella lenta is an anaerobic, Gram-positive bacillus commonly found in the human digestive tract. Occasionally, it can cause life-threatening infections. Bacteremia due to this organism is always clinically significant and is associated with gastrointestinal diseases and states of immune suppression. The authors report a case involving an elderly man with a newly diagnosed gastrointestinal malignancy who developed bacteremia caused by E lenta, treated successfully using empirical therapy with vancomycin and piperacillin-tazobactam, followed by directed therapy with metronidazole once the identity and antibiotic susceptibility of the organism was established. The present case reinforces the connection between E lenta bacteremia with gastrointestinal malignancy and highlights the importance of searching for a source of bacteremia due to this organism.

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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0040.002
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 head0.004
GPT teacher head0.217
Teacher spread0.212 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

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