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Record W4412491371 · doi:10.1002/rcr2.70283

Asbestosis Requiring Lung Transplantation in a Retired Hairdresser: An Occupational Exposure to Comb Through

2025· article· en· W4412491371 on OpenAlexaff
稔雄 阿部, Lakshmi Puttagunta, K. Halloran, J. Weinkauf, Dale Lien, Bryce Laing, Eric C. Leung, Doug Helmersen, Mitesh V. Thakrar, A. Hirji

Bibliographic record

VenueRespirology Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversity of Manitoba
Fundersnot available
KeywordsAsbestosisLung transplantationMedicineInterstitial lung diseaseAsbestosOccupational lung diseaseDiseaseOccupational diseaseIntensive care medicineLungOccupational exposurePathologyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Asbestosis is a form of fibrotic interstitial lung disease caused by the inhalation of excessive asbestos fibres. We describe a patient who developed asbestosis due to occupational exposures while working as a hairdresser in the 1970s and 1980s. Not appreciating this profession as a risk factor for developing asbestosis led to several treatment strategies that were ineffective and eventually led to the need for lung transplantation. More recent changes to governmental policy have effectively reduced the incidence of such an exposure risk; however, given the long latency of the disease, we emphasise that a broad occupational history including potential historic exposures remains an important component of the assessment of interstitial lung disease. We also outline many reasons for a second wave of asbestosis-related lung disease that is only now emerging and encourage clinicians to continue to maintain asbestosis on the differential for working up undifferentiated fibrotic lung disease.

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)0.001
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 score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0050.004
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 head0.019
GPT teacher head0.339
Teacher spread0.320 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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