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Record W3115169998 · doi:10.1016/j.idcr.2020.e01034

Whole genome sequence of Corynebacterium kroppenstedtii isolated from a case of recurrent granulomatous mastitis

2020· article· en· W3115169998 on OpenAlexaff
Charlie Tan, Fang‐I Lu, Patryk Aftanas, Kara K. Tsang, Samira Mubareka, Adrienne K. Chan, Robert Kozak

Bibliographic record

VenueIDCases · 2020
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreMcMaster UniversitySunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsGranulomatous mastitisMastitisWhole genome sequencingMedicineCorynebacteriumDNA sequencingGenomePathologyBiologyGeneGeneticsBacteria

Abstract

fetched live from OpenAlex

We describe the case of a 33-year-old woman with recurrent granulomatous mastitis associated with Corynebacterium kroppenstedtii. This organism has been increasingly associated with granulomatous mastitis, specifically the cystic neutrophilic histopathologic variant, although currently there is a paucity both of reported cases and genomic sequence data. We highlight the challenges in the diagnosis and treatment of this entity, in particular focusing on the various methods of microbiologic identification, including MALDI-TOF, 16 s rRNA PCR and whole-genome sequencing.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.308
Teacher spread0.248 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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