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Record W2118369893 · doi:10.1111/anae.13070

Dominant hand operating probe vs needle: a comparison study of ultrasound‐guided needle placement in phantom models

2015· article· en· W2118369893 on OpenAlexaff
D. Johnston, Michael A. Stafford

Bibliographic record

VenueAnaesthesia · 2015
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineImaging phantomUltrasoundNuclear medicineRadiologyBiomedical engineering

Abstract

fetched live from OpenAlex

We conducted a replicated crossover design study to assess if using one's dominant hand for operating a probe vs directing a needle would affect the time taken, the number of needle passes and the accuracy of an ultrasound-guided procedure in phantom models. Twenty ultrasound-novice participants completed the task 10 times for each hand arrangement (alternating between attempts). The time taken and number of needle passes required for both dominant hand-probe and hand-needle decreased over time (p = 0.001). Dominant hand-needle had a lower mean time used (p = 0.001) and fewer needle passes (p = 0.02) compared with hand-probe. Sixty-five per cent of participants preferred using their dominant hand to direct the needle. When learning ultrasound-guided needle procedures on phantom models, use of the dominant hand to operate the needle is associated with a shorter procedure time and fewer needle passes.

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)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.349
Teacher spread0.250 · 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 designBench or experimental
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

Citations9
Published2015
Admission routes1
Has abstractyes

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