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Record W2067767953 · doi:10.7899/1042-5055-26.1.47

A Comparative Analysis of Sonographic Interpretation of Peripheral Nerves in the Anterior Compartment of the Forearm Between an Experienced and Novice Interpreter

2012· article· en· W2067767953 on OpenAlexaff
Laurie Y. Hung, Octavian C. Lucaciu, David Soave

Bibliographic record

VenueJournal of Chiropractic Education · 2012
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsPeripheralForearmInterpreterComputer scienceInterpretation (philosophy)MedicineAnatomyCompartment (ship)Internal medicine

Abstract

fetched live from OpenAlex

PURPOSE: This article describes a pilot study that compares the ability of a novice interpreter and an experienced interpreter to interpret ultrasound images of peripheral nerves in the anterior compartment of the forearm. METHODS: Twenty subjects between 18 and 50 years of age were included. A student was taken through tutorials in which she was guided through identification of the peripheral nerves of the anterior forearm. After the tutorials, the experienced interpreter traced the subjects' ulnar nerve and artery neurovascular bundle proximally in the anterior compartment of the forearm until just before it separated into the artery and nerve. Here the distance between the median and ulnar nerve was measured by the investigators. The Bland and Altman design and paired t tests were used to compare the agreement between the results of the two investigators. RESULTS: The Bland and Altman analysis reveals that the difference between two sets of measurements (experienced investigator vs. student) is calculated to be 0.08 mm ± 0.22 mm for the left arm and 0.16 mm ± 0.43 mm for the right arm. A paired t test revealed that there is no significant difference in the measurements obtained by the two investigators (left arm: p = .12; right arm: p = .10). These results suggest that the measurements of the two investigators may be interchangeable. CONCLUSIONS: This pilot study shows that after tutorials combining dissection and sonographic interpretation, the ability of a novice interpreter to identify ultrasonographic images of peripheral nerves in the anterior compartment of the forearm is comparable to that of an experienced interpreter.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.385
Teacher spread0.351 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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