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Record W126860265 · doi:10.1155/2004/729689

Granulomatous Bronchiolitis with Necrobiotic Pulmonary Nodules in Chrohn's Disease

2004· article· en· W126860265 on OpenAlexafffundvenue
Hugh James Freeman, Jennifer Davis, Marcia E Prest, Edward J. Lawson

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2004
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsSurrey Memorial HospitalUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsBronchiolitisMedicinePneumoniaPathologyLungBronchiolitis obliteransPathologicalGranulomaImmunosuppressionChronic granulomatous diseaseRespiratory systemInternal medicineImmunologyLung transplantation

Abstract

fetched live from OpenAlex

A 37-year-old man with extensive Crohn's disease of the stomach, small and large intestine for almost a decade developed respiratory symptoms and radiological findings suggestive of pneumonia that failed to resolve with antibiotic treatment. Computed tomography scanning of his lungs showed extensive changes with cavitated parenchymal nodules. Histological evaluation of an open lung biopsy showed granulomatous bronchiolitis and pulmonary necrobiosis. Treatment with steroids and immunosuppression resulted in complete resolution of his clinical symptoms of pneumonia and abnormal computed tomography imaging changes. Granulomatous bronchiolitis and necrobiotic nodules may be a manifestation of Crohn's disease in the absence of microbial agents, including mycobacteria or fungal agents. While a multiplicity of complex pulmonary changes may occur in Crohn's disease, their clinical recognition and precise pathological definition may be particularly important if treatment with a biological agent, such as infliximab, is being considered.

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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations37
Published2004
Admission routes3
Has abstractyes

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