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Record W3175625279 · doi:10.22374/cjgim.v16i2.507

Minimal Criteria for Lung Ultrasonography in Internal Medicine

2021· article· en· W3175625279 on OpenAlex
Janeve Desy, Vicki E. Noble, Andrew S. Liteplo, Paul Olszynski, Brian Buchanan, Renee K. Dversdal, Shane Arishenkoff, Gigi Liu, Elaine Dumoulin, Irene Ma

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity of British ColumbiaUniversity of AlbertaUniversity of SaskatchewanUniversity of Calgary
Fundersnot available
KeywordsMedicinePrimary careUltrasonographyGynecologySurgeryFamily medicine

Abstract

fetched live from OpenAlex

BackgroundPoint-of-care lung ultrasound (LUS) examination is increasingly utilized in Internal Medicine. To improve the standardization of LUS education and clinical use, explicit minimal criteria for defining what is an acceptable and clinically useful image are needed.MethodsA 97-item online survey of potential minimal criteria for common uses of LUS in Internal Medicine was developed and sent to 10 international point-of-care ultrasound experts. Their opinion on the inclusion of each item was sought and items not achieving consensus (defined as agreement by at least 70% of the experts) were reassessed in subsequent rounds. A total of three rounds were conducted.ResultsSeventy-four minimal criteria were agreed upon for inclusion, 24 were agreed upon for exclusion, and two did not reach consensus.ConclusionsExperts agreed on 74 minimal criteria for Internal Medicine LUS. The use of these minimal criteria during teaching and clinical use is strongly recommended. RésuméContexteL’échographie pulmonaire au point d’intervention est de plus en plus utilisée en médecine interne. Pour améliorer l’uniformisation de la formation sur l’échographie pulmonaire et de son utilisation clinique, il faut des critères minimaux explicites pour définir ce qu’est une image acceptable et utile sur le plan clinique.MéthodologieUn sondage en ligne de 97 éléments portant sur des critères minimaux possibles dans l’utilisation courante de l’échographie pulmonaire en médecine interne a été élaboré et soumis à 10 experts internationaux en échographie au point d’intervention. Leur avis sur l’inclusion de chaque élément a été sondé, et les éléments pour lesquels il n’y avait pas de consensus (défini par l’accord d’au moins 70 % des experts) ont été réévalués lors de tours suivants. Au total, trois tours ont été effectués.RésultatsSoixante-quatorze critères minimaux ont été acceptés, 24 ont été exclus et deux n’ont pas fait consensus.ConclusionsLes experts se sont entendus sur 74 critères minimaux relatifs à l’échographie pulmonaire en médecine interne. L’utilisation de ces critères minimaux au cours de l’enseignement et de l’utilisation clinique est fortement recommandée.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.381
Teacher spread0.330 · 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