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Record W2189034836 · doi:10.1183/13993003.01132-2015

Towards the standardisation of lung sound nomenclature

2015· article· en· W2189034836 on OpenAlexaff
Hans Pasterkamp, Paul L.P. Brand, Mark L. Everard, Luis García‐Marcos, Hasse Melbye, Kostas Ν. Priftis

Bibliographic record

VenueEuropean Respiratory Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicPhonocardiography and Auscultation Techniques
Canadian institutionsUniversity of Manitoba
FundersMedizinische Universität GrazAssistance publique-Hôpitaux de ParisKarl-Franzens-Universität GrazMedicinski Fakultet, Sveučilište u ZagrebuUniversità degli Studi di FerraraUniversidade do PortoUniversidade Nova de LisboaUniversité Paris DiderotUniversitetet i OsloWarszawski Uniwersytet MedycznyUniversidad Autónoma de MadridNational and Kapodistrian University of AthensKarolinska InstitutetUniwersytet WarszawskiKocaeli ÜniversitesiUniversité de StrasbourgLeids Universitair Medisch CentrumUniversität zu LübeckCentre Hospitalier Universitaire de BordeauxUniversiteit LeidenUniversity of PatrasAarhus UniversitetshospitalUniversity of CyprusCyprus University of TechnologyUniversidad de MurciaSveučilište u ZagrebuEuropean Respiratory SocietyUniversità degli Studi di MilanoInstituto De Saúde Pública, Universidade do PortoMarmara ÜniversitesiUniversitat de BarcelonaGöteborgs UniversitetRadboud UniversiteitAarhus UniversitetUniverzita Karlova v Praze
KeywordsNomenclatureTerminologyAuscultationTask forceTask (project management)Sound (geography)Data collectionComputer scienceMedicineNatural language processingLinguisticsAcousticsRadiologyEngineeringTaxonomy (biology)MathematicsBiology

Abstract

fetched live from OpenAlex

Auscultation of the lung remains an essential part of physical examination even though its limitations, particularly with regard to communicating subjective findings, are well recognised. The European Respiratory Society (ERS) Task Force on Respiratory Sounds was established to build a reference collection of audiovisual recordings of lung sounds that should aid in the standardisation of nomenclature. Five centres contributed recordings from paediatric and adult subjects. Based on pre-defined quality criteria, 20 of these recordings were selected to form the initial reference collection. All recordings were assessed by six observers and their agreement on classification, using currently recommended nomenclature, was noted for each case. Acoustical analysis was added as supplementary information. The audiovisual recordings and related data can be accessed online in the ERS e-learning resources. The Task Force also investigated the current nomenclature to describe lung sounds in 29 languages in 33 European countries. Recommendations for terminology in this report take into account the results from this survey.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.065
GPT teacher head0.318
Teacher spread0.253 · 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 designNot applicable
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

Citations131
Published2015
Admission routes1
Has abstractyes

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