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Record W4415476926 · doi:10.1183/23120541.00732-2025

Effect of transient <i>versus</i> persistent <i>Aspergillus</i> colonisation on clinical outcomes in bronchiectasis

2025· article· en· W4415476926 on OpenAlexaff
Allison Michaud, Julie Jarand, Christina S. Thornton

Bibliographic record

VenueERJ Open Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColonizationBronchiectasisSputumAllergic bronchopulmonary aspergillosisDiseaseColonisationInflammationCystic fibrosis

Abstract

fetched live from OpenAlex

<title>Extract</title> Bronchiectasis is a chronic pulmonary disorder characterized by irreversible dilatation of the bronchi, leading to chronic cough, sputum production, and recurrent respiratory infections [1]. Among the pathogens colonizing the airways of patients with bronchiectasis, <italic>Aspergillus</italic> species are notable due to their potential to exacerbate inflammation and contribute to disease progression [2]. While colonization by <italic>Aspergillus</italic> is recognized in bronchiectasis [3, 4], the differential impact of transient <italic>versus</italic> persistent colonization on clinical outcomes is not well understood. The presence of <italic>Aspergillus</italic> in the airways can range from transient colonization, where the fungus is intermittently present, to persistent colonization, characterized by continuous presence over time [3, 4]. Understanding the implications of these colonization patterns is crucial for guiding clinical management and therapeutic interventions. Outside of allergic bronchopulmonary aspergillosis (ABPA) [5], this has not been systemically evaluated in bronchiectasis. We aimed to evaluate the effects of transient and persistent <italic>Aspergillus</italic> colonization on clinical outcomes in bronchiectasis, hypothesizing that persistent colonization would be associated with worse outcomes.

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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.124
GPT teacher head0.519
Teacher spread0.395 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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