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Record W4412649670 · doi:10.1055/a-2664-6541

Thoracic Ultrasound – EFSUMB Training Recommendations – a Position Paper

2025· article· en· W4412649670 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUltraschall in der Medizin - European Journal of Ultrasound · 2025
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsUltrasoundCompetence (human resources)MedicineMedical physicsPsychological interventionClinical PracticeRadiologyPhysical therapyNursingPsychology

Abstract

fetched live from OpenAlex

A wide range of medical specialists increasingly use thoracic ultrasound and transthoracic ultrasound-guided interventions in their clinical practice. To ensure high quality and standardized practice across specialties, this position paper of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) describes the training requirements for thoracic ultrasound. The recommendations follow the three EFSUMB competency levels for medical ultrasound practice. Level 1 describes the skills required to perform basic thoracic ultrasound examinations and basic interventions independently, level 2 includes more advanced transthoracic ultrasound imaging and guided interventions, while level 3 involves the practice of high-level thoracic ultrasound and the use of advanced technologies. Previously, a predefined minimum number of ultrasound examinations was used to determine competence, but in recent years, a general shift towards competency-based training and assessment has been implemented. For each EFSUMB level, we outline the theoretical knowledge and practical skills needed for clinical practice.

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.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.364
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