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Record W2413501364 · doi:10.1097/id.0000000000000354

The Onward March of Implant-Related Technology

2015· editorial· en· W2413501364 on OpenAlexaboutno aff
Morton L. Perel

Bibliographic record

VenueImplant Dentistry · 2015
Typeeditorial
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsImplantComputer scienceRoboticsDental implant3D printingRobotArtificial intelligenceDentistryMedicineMedical physicsEngineeringSurgeryMechanical engineering

Abstract

fetched live from OpenAlex

Whether by heuristically driven trial and error or by algorithmically defined mathematical certainty, the hackneyed expression “the future is now” is alive, and being fulfilled, in the field of implant dentistry/oral implantology. Examples abound. Three-dimensional (3D) printing has had an auspicious introduction in the medical profession with programs such as The First Bioprinting Event in Singapore in 2014. 3D printing in the practice of implant dentistry is especially noteworthy in the fabrication of surgical guides. To facilitate precise implant insertions, computer software based on computer tomography data of the anticipated site, of either the maxilla or the mandible, is seamlessly followed by 3D printing of a model and its digital successor…a surgical guide. Now, let us go back a couple of years to an article titled “Automated Dental Implantation Using Image-Guided Robotics: Registration Results.”1 The purpose section within the authors' abstract is worth quoting. It seems to be an extension of the 3D printing rationale. “One of the most important factors affecting the outcome of dental implantation is the accurate insertion of the implant into the patient's jaw bone, which requires a high degree of anatomical accuracy. With the accuracy and stability of robots, image-guided robotics is expected to provide more reliable and successful outcomes for dental implantation. Here, we proposed the use of a robot for drilling the implant site in preparation for the insertion of the implant.” Our continuing journey through biotechnology brings us to the shape-memory properties of SMPs. Dr. L'Hocine Yahia of the Polytechnique Montréal, whose expertise includes bioengineering and biosystems engineering, has described this emerging class of smart polymers. The sutures that are light-activated, thermally induced, and biodegradable enable wound healing that avoids tissue damage by being self-adjusting so as to have optimal tension without over-tightening. His book Shape Memory Polymers for Biomedical Applications2 is a classic…current, yet futuristic. Adding to our advances in technology is the invention by Dr. Assad Mora who has pioneered a new era in visualization technology. He has introduced MoraVision™ 3D system that is stereoscopic 3D video technology for viewing accurate 3D depth perception while the operator/clinician sits straight without having to bend to see what he/she is performing, either surgically or prosthetically, in the mouth. It is a powerful ergonomically positive that speaks to the avoidance of operator self-induced back and back-related ailments. Do the above technological advancements not make us think, in a rather tongue-in-cheek manner, of the creation of drive-through implant tooth replacements? Perish the thought. Fortunately for our patients, innovators, inventors, and researchers have ascended the technological ladder that is directly, or tangentially, related to implant dentistry.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.331
Teacher spread0.314 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2015
Admission routes1
Has abstractyes

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