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Record W2124879124 · doi:10.1183/09031936.05.00035205

Interpretative strategies for lung function tests

2005· article· de· W2124879124 on OpenAlexfundno aff
Raffaello Pellegrino, Giovanni Viegi, Vito Brusasco, Robert O. Crapo, Felip Burgos, Richard Casaburi, Allan L. Coates, C.P.M. van der Grinten, Per Gustafsson, J. Hankinson, Robert L. Jensen, David C. Johnson, Neil R. MacIntyre, Ryan T. McKay, Martin R. Miller, Daniel Navajas, Ole Pedersen, Jack Wanger

Bibliographic record

VenueEuropean Respiratory Journal · 2005
Typearticle
Languagede
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
FundersHospital for Sick ChildrenUniversity Hospitals Birmingham NHS Foundation TrustMassachusetts General Hospital
KeywordsMedicineSpirometryPulmonary function testingLung functionPulmonary medicineInterpretation (philosophy)Diffusing capacityLungLung volumesTest (biology)Medical physicsIntensive care medicinePhysical therapyRadiologyInternal medicineComputer scienceAsthma

Abstract

fetched live from OpenAlex

BACKGROUNDThis section is written to provide guidance in interpreting pulmonary function tests (PFTs) to medical directors of hospital-based laboratories that perform PFTs, and physicians who are responsible for interpreting the results of PFTs most commonly ordered for clinical purposes.Specifically, this section addresses the interpretation of spirometry, bronchodilator response, carbon monoxide diffusing capacity (DL,CO) and lung volumes.The sources of variation in lung function testing and technical aspects of spirometry, lung volume measurements and DL,CO measurement have been considered in other documents published in this series of Task Force reports [1-4] and in the American Thoracic Society (ATS) interpretative strategies document [5].An interpretation begins with a review and comment on test quality.Tests that are less than optimal may still contain useful information, but interpreters should identify the problems and the

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)0.118
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: Methods · Consensus signal: Methods
Teacher disagreement score0.040
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.118
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.002
Science and technology studies0.0020.002
Scholarly communication0.0080.007
Open science0.0040.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0400.025

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 head0.031
GPT teacher head0.327
Teacher spread0.295 · 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
GenreMethods

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

Citations5,976
Published2005
Admission routes1
Has abstractyes

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