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Record W4405485355 · doi:10.29007/ldml

Potential for Reducing Radiation Dose in Proximal Tibia Plate Fixation Using Depth Camera Augmented Fluoroscopy (DeCAF)

2024· article· en· W4405485355 on OpenAlexfundno aff
Parinaz Ranjbaran, Pierre Guy, David J. Stockton, Antony J. Hodgson

Bibliographic record

VenueEPiC series in health sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaInstitute for Computing, Information and Cognitive Systems
KeywordsFluoroscopyFixation (population genetics)Radiation doseMedicineNuclear medicineRadiology

Abstract

fetched live from OpenAlex

Mobile C-arm x-ray machines are commonly used in orthopaedic trauma surgeries to visualize internal anatomy. However, the use of scouting images to aid C-arm positioning during these procedures can prolong operating time and increase radiation exposure. Our Depth Camera Augmented Fluoroscopy (DeCAF) device is designed to reduce the number of x-ray images needed by overlaying the fluoroscopic images onto a live video of the patient’s surface anatomy. In this study, we demonstrate in a simulated operating room (OR) environment that the DeCAF system has clinically acceptable overlay accuracy (1.3 ± 0.2 mm) and allowed the surgeon to substantially eliminate use of x-rays while fixing proximal tibial plates in acceptable positions without significantly changing the time required (p = 0.72). This justifies proceeding to live clinical evaluations.

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)0.001
metaresearch head score (Gemma)0.004
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.381
Teacher spread0.344 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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