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Record W2146965595 · doi:10.1183/09031936.05.00035005

Standardisation of the measurement of lung volumes

2005· review· en· W2146965595 on OpenAlexfundno aff
Jack Wanger, Jack L. Clausen, Allan L. Coates, Ole Pedersen, Vito Brusasco, Felip Burgos, Richard Casaburi, Robert O. Crapo, Paul Enright, C.P.M. van der Grinten, Per Gustafsson, J. Hankinson, Robert L. Jensen, Douglas C. Johnson, Neil R. MacIntyre, Ryan T. McKay, Martin R. Miller, Daniel Navajas, Raffaello Pellegrino, Giovanni Viegi

Bibliographic record

VenueEuropean Respiratory Journal · 2005
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
FundersNational Institute for Occupational Safety and HealthNational Heart, Lung, and Blood InstituteUniversiteit LeidenHospital for Sick ChildrenUniversitat de BarcelonaUniversity Hospitals Birmingham NHS Foundation TrustUniversity of MiamiUniversity of California, San DiegoMassachusetts General Hospital
KeywordsMedicineMedical physics

Abstract

fetched live from OpenAlex

This is a document produced by a joint ATS-ERS Task Force on lung function testing to provide new combined standards for lung volume measurements. It largely reflects a document that was produced after an international workshop held in 1990, funded by the National Heart Lung and Blood Institute (NHLBI). That document was very large and never published in full print, but those interested in all the details can find it posted on the ATS website. In the new document, the relevant technical aspects and the limitations of the methods currently available for lung volume measurements are summarised in a user-friendly way. The position of lung volume measurements in the diagnosis of respiratory disorders and their cost-to-benefit ratio were probably the most controversial aspects of the Task Force.

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)0.029
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0050.003
Science and technology studies0.0000.003
Scholarly communication0.0030.004
Open science0.0050.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.003

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 head0.084
GPT teacher head0.357
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2,779
Published2005
Admission routes1
Has abstractyes

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