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Record W4379876089 · doi:10.1002/ccr3.7490

Long‐standing laryngeal rhinoscleroma with rare Mikulicz cells

2023· article· en· W4379876089 on OpenAlexaff
Raheem Peerani, Manish A. Shah, Brian Minnema, Hasan Ghaffar, Runjan Chetty, Jan Delabie, Bayardo Perez‐Ordoñez, Daniel Xia

Bibliographic record

VenueClinical Case Reports · 2023
Typearticle
Languageen
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsUniversity Health NetworkSt. Michael's HospitalNorth York General HospitalUniversity of Toronto
Fundersnot available
KeywordsRhinoscleromaMedicinePathognomonicPathologyGranulomatous diseaseSarcoidosisDermatologyDisease

Abstract

fetched live from OpenAlex

Rhinoscleroma is an infectious granulomatous disease. It is important to identify pathognomonic Mikulicz cells on microscopy, as these can be rare and the chronic inflammatory infiltrate can appear otherwise nonspecific on biopsies.

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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.109
GPT teacher head0.402
Teacher spread0.293 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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