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Record W4385858843 · doi:10.1093/ofid/ofad436

Schrödinger's Cat Paradox: <i>Bartonella</i> Serology Cannot Be Used to Speciate <i>Bartonella</i> Endocarditis

2023· article· en· W4385858843 on OpenAlexaff
Carl Boodman, Nitin Gupta

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBartonella species infections research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBartonellaSerologyEndocarditisBartonella henselaeVirologyMedicineMicrobiologyCat-scratch diseaseBiologyImmunologyPathologyDiseaseInternal medicineAntibody

Abstract

fetched live from OpenAlex

We read with great interest Ordaya et al.'s recent article titled "Let the Cat out of the Heart", describing the clinical characteristics of 16 cases of Bartonella endocarditis.We congratulate the authors on an intriguing case series that highlights Bartonella endocarditis's association with renal failure, embolization and PR3-ANCA positivity.Publishing case-level data on Bartonella endocarditis is increasingly relevant in light of the 2023 updates to the Modified Duke criteria that include Bartonella diagnostics as a major endocarditis criterion.[1]However, we have concerns that the article, including the witty title, may mislead readers to consider B. henselae as the predominant etiology of Bartonella endocarditis without providing species-level evidence to support this claim.The 16 cases described were diagnosed by Bartonella serologic positivity, with seven patients confirmed to Bartonella genus-level by Bartonella PCR on explanted cardiac tissue.Species-specific PCR targets such as 16S rRNA, ribC, rpoB and gltA genes were not performed.[2]While the authors mention Bartonella species other than B. henselae in the introduction, they proceed to focus on B. henselae, emphasizing cat exposure and Ctenocephalides flea vectors."Cat exposure" was reported in 62.5% of the described cases, but the authors failed to define what this exposure meant.Were all "cat exposures" scratches or simply a recollection of a feline in the vicinity?The authors also failed

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.026

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 head0.030
GPT teacher head0.310
Teacher spread0.280 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations7
Published2023
Admission routes1
Has abstractyes

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