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Record W4412879352 · doi:10.1016/j.xjon.2025.07.003

Surgical gloves need a better fit: Promoting equity in operating rooms

2025· article· en· W4412879352 on OpenAlexaff
Hamnah Majeed, Emmanuel Moss, Haris Majeed, Jae Byun, Eslem Altın, Bobby Yanagawa

Bibliographic record

VenueJTCVS Open · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsSt. Michael's HospitalMcGill University Health CentreJewish General HospitalUniversity of Toronto
Fundersnot available
KeywordsSurgical GlovesEquity (law)Surgical proceduresBusinessMedicineSurgeryPolitical science

Abstract

fetched live from OpenAlex

The first surgical gloves were created by the Goodyear Rubber Company in 1889 to protect the hands of the female head scrub nurse of Dr William Halsted. Women generally have smaller hands compared with men, with the median glove size being 6.0 versus 7.5, respectively, among surgeons.1 Despite anatomic differences in male and female hand measurements, there exists a paucity of research regarding the fit of these gloves. Improper glove sizing could result in musculoskeletal pain, reduced fine motor performance, and dissatisfaction.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.157
GPT teacher head0.559
Teacher spread0.402 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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