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Record W4283009277 · doi:10.3390/app12126153

How to Create and 3D Print a Model of the Skull and Orbit for Craniomaxillofacial Surgeons

2022· article· en· W4283009277 on OpenAlexaff
Léonard Bergeron, Jordan Gornitsky, Michelle Bonapace-Potvin

Bibliographic record

VenueApplied Sciences · 2022
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsSplintsComputer science3d printer3D printingSkullProcess (computing)Software3d modelComputer graphics (images)Engineering drawingMultimediaHuman–computer interactionMedicineArtificial intelligenceOrthodonticsEngineeringSurgeryMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Three-dimensional (3D) anatomical models are used in many ways in cranio-maxillo-facial (CMF) surgery, including being used to press-fit plates, mold splints, and for student teaching. Their use has many advantages, including the possibility of lowering operative time and allowing for more precise reconstructions with personalized plates, meshes, and splints. This can now be done in-house to speed up model availability for trauma surgery as well. Three-dimensional printers and software are quickly evolving—printers now are easily accessible, and the models are inexpensive to print. However, for a surgeon with no IT training, 3D printing even a simple anatomic model may be a challenge. The purpose of this article is to offer simple, step-by-step video tutorials demonstrating the process of extracting a CMF model from a patient CT scan, doing basic manipulation to the model, and then printing it in-house with a prosumer grade 3D printer. It is our hope that this user-friendly article will allow more surgeons and scientists to use 3D printing and its advantages.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.137

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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