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Evidence for dysanapsis using computed tomographic imaging of the airways in older ex-smokers

2009· article· en· W2045097725 on OpenAlexafffund
A. William Sheel, Jordan A. Guenette, Ren Yuan, L Holy, John R. Mayo, Annette McWilliams, Stephen Lam, Harvey O. Coxson

Bibliographic record

VenueJournal of Applied Physiology · 2009
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsBC Cancer AgencyVancouver General HospitalSt. Paul's HospitalUniversity of British Columbia
FundersNational Cancer InstituteNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsComputed tomographicComputed tomographyMedicineNuclear medicineRadiology

Abstract

fetched live from OpenAlex

We sought to determine the relationship between lung size and airway size in men and women of varying stature. We also asked if men and women matched for lung size would still have differences in airway size and if so where along the pulmonary airway tree would these differences exist. We used computed tomography to measure airway luminal areas of the large and central airways. We determined airway luminal areas in men (n = 25) and women (n = 25) who were matched for age, body mass index, smoking history, and pulmonary function and in a separate set of men (n = 10) and women (n = 11) who were matched for lung size. Men had greater values for the larger airways and many of the central airways. When male and female subjects were pooled there were significant associations between lung size and airway size. Within the male and female groups the magnitudes of these associations were decreased or nonsignificant. In males and females matched for lung size women had significantly smaller airway luminal areas. The larger conducting airways in females are significantly smaller than those of males even after controlling for lung size.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.332
Teacher spread0.294 · 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 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

Citations142
Published2009
Admission routes2
Has abstractyes

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Same venueJournal of Applied PhysiologySame topicChronic Obstructive Pulmonary Disease (COPD) ResearchFrench-language works237,207