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Record W2114263671 · doi:10.1183/09031936.06.00070805

Computed tomographic estimation of lung dimensions throughout the growth period

2006· article· en· W2114263671 on OpenAlexaff
Pim A. de Jong, Frederick R. Long, Janice Wong, Peter Merkus, Harm A.W.M. Tiddens, James C. Hogg, Harvey O. Coxson

Bibliographic record

VenueEuropean Respiratory Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsVancouver General HospitalSt. Paul's Hospital
Fundersnot available
KeywordsAirwayLumen (anatomy)ParenchymaLungMedicineBody surface areaComputed tomographyLung volumesRadiologyComputed tomographicCardiologyInternal medicinePathologySurgery

Abstract

fetched live from OpenAlex

The aim of the current study was to use computed tomography (CT) to estimate airway wall and lumen, and arterial and parenchyma dimensions in children throughout the growth period, and to provide normative data to study alterations caused by pulmonary disease. Clinical CT scans reported as normal that were performed in children for nonpulmonary and noncardiac reasons were analysed for lung weight, gas volume, lung expansion, lung surface/volume ratio, airway wall area, airway lumen area, airway lumen perimeter, arterial area and airway surface length/area ratio. The age range of the 50 subjects was 0-17.2 yrs. The data showed only little increase in lung expansion throughout childhood (n = 32). There was substantial variability in lung expansion between subjects. Airway wall and lumen and arterial area were exponentially associated with subjects' height (n = 50). Airway surface length/area ratio was linearly associated to alveolar surface/volume ratio. The data from the current study provide normative computed tomography estimates of airway wall and lumen, and arterial and parenchyma dimensions throughout the growth period that may be useful for the study of alterations in 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 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)0.002
metaresearch head score (Gemma)0.000
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 score0.449
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.351
Teacher spread0.316 · 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

Citations48
Published2006
Admission routes1
Has abstractyes

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