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Record W2587495793 · doi:10.1111/vru.12479

INTRAOPERATIVE IMAGE NAVIGATION: EXPERIMENTAL STUDY OF THE FEASIBILITY AND SURGEON PREFERENCE BETWEEN A STERILE ENCASED NINTENDO WII<sup>TM</sup> REMOTE AND STANDARD WIRELESS COMPUTER MOUSE

2017· article· en· W2587495793 on OpenAlexaff
Ryan Appleby, Alex zur Linden, William Sears

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2017
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Guelph
FundersLG Electronics
KeywordsMedicineMedical physicsInstitutional review boardAcademic institutionSurgeryComputer science

Abstract

fetched live from OpenAlex

Diagnostic imaging plays an important role in the operating room, providing surgeons with a reference and surgical plan. Surgeon autonomy in the operating room has been suggested to decrease errors that stem from communication mistakes. A standard computer mouse was compared to a wireless remote-control style controller for computer game consoles (Wiimote) for the navigation of diagnostic imaging studies by sterile personnel in this prospective survey study. Participants were recruited from a cohort of residents and faculty that use the surgical suites at our institution. Outcome assessments were based on survey data completed by study participants following each use of either the mouse or Wiimote, and compared using an analysis of variance. The mouse was significantly preferred by the study participants in the categories of handling, accuracy and efficiency, and overall satisfaction (P <0.05). The mouse was preferred to both the Wiimote and to no device, when participants were asked to rank options for image navigation. This indicates the need for the implementation of intraoperative image navigation devices, to increase surgeon autonomy in the operating room.

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)0.000
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 score0.059
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.090
GPT teacher head0.348
Teacher spread0.259 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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