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Record W2413310961 · doi:10.1055/s-2004-815605

Bronchiolitis Caused by Occupational and Ambient Atmospheric Particles

2003· article· en· W2413310961 on OpenAlexaff
Andrew Churg

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineBronchiolitisAirwayFibrosisAsbestosPathologyHyperplasiaAirway obstructionPulmonary fibrosisParticulatesAir pollutantsRespiratory tractRespiratory systemAir pollutionInternal medicineSurgeryMetallurgyChemistry

Abstract

fetched live from OpenAlex

Occupationally encountered mineral dusts such as asbestos, silica, silicates (talc, mica), and metals can produce a distinctive pattern of fibrosis and distortion of the small airways, particularly the distal membranous bronchioles (MB) and the respiratory bronchioles (RB). Recent reports show that the same types of changes, accompanied by considerable muscle hyperplasia, are found in individuals living in regions with high levels of particulate air pollutants (PM). Models and actual measurements suggest that these changes occur because the small airways are sites of high particle deposition, and inhaled and deposited particulates, including PM, enter the airway walls. Studies from our laboratory using a tracheal explant model have shown that, for many types of particles, entry into the airway wall causes expression of mediators that lead to airway wall fibrosis and airway wall smooth muscle hyperplasia, probably through oxidant mechanisms. These reactions are intrinsic properties of the particles and do not require exogenous inflammatory cells. There is considerable evidence that individuals with occupational exposure to a wide variety of mineral dusts, as well as individuals with chronic exposure to high levels of PM, develop chronic airflow obstruction. The type of small airway remodeling seen in particle-induced bronchiolitis appears to be one cause of chronic airflow obstruction in this setting.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.030
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.301
Teacher spread0.285 · 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

Citations25
Published2003
Admission routes1
Has abstractyes

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