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Record W1831432884 · doi:10.1093/milmed/168.4.312

Rapid Diagnosis of an Ulnar Fracture with Portable Hand-Held Ultrasound

2003· article· en· W1831432884 on OpenAlexaff
Andrew W. Kirkpatrick, Ross Brown, Lawrence N. Diebel, Savvas Nicolaou, Tom Marshburn, Scott A. Dulchavsky

Bibliographic record

VenueMilitary Medicine · 2003
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsCanadian Armed ForcesVancouver Hospital and Health Sciences CentreFoothills Medical Centre
Fundersnot available
KeywordsMedicineUltrasoundOrthopedic surgeryFracture (geology)RadiologySurgeryBiomedical engineeringGeology

Abstract

fetched live from OpenAlex

Orthopedic fractures are a common injury in operational activities, which are injuries that often occur in isolated or hostile environments. Clinical ultrasound devices have become more user-friendly and lighter, allowing them to be easily transported with forward medical teams. The bone-soft tissue interface has a very large acoustic impedance with a high reflectance that can be used to visualize breaks in contour including fractures. Herein reported is a case of an ulnar fracture that was quickly visualized in the early phase of a multisystem trauma resuscitation with a hand-held ultrasound device. The implications for operational medicine are discussed.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.355
Teacher spread0.319 · 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 designObservational
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

Citations22
Published2003
Admission routes1
Has abstractyes

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