MétaCan
Menu
Back to cohort
Record W4391469932 · doi:10.3390/medicina60020260

Expediting the Rehabilitation of Severely Resorbed Ridges Using a Combination of CAD-CAM and Analog Techniques: A Case Report

2024· article· en· W4391469932 on OpenAlexaff
Carlos A. Jurado, Francisco X. Azpiazu‐Flores, Chin‐Chuan Fu, Silvia Rojas‐Rueda, Gerardo Guzman‐Perez, Franciele Floriani

Bibliographic record

VenueMedicina · 2024
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineDenturesRehabilitationCADDentistryExpeditingQuality of life (healthcare)RetrievabilityOrthodonticsComputer scienceEngineeringEngineering drawingPhysical therapy

Abstract

fetched live from OpenAlex

With the life expectancy increasing, there is a growing need for prosthetic dental treatments to restore the oral health, function, and quality of life of edentulous patients. Presently, only a few articles are available describing the oral rehabilitation of patients with severely resorbed ridges with milled complete dentures. This clinical case report provides a straightforward protocol consisting of a combination of analog and digital techniques for the rehabilitation of edentulous patients with severely resorbed ridges with milled fixed and removable complete dentures. This technique permits the minimization of the number of appointments, improves patient comfort, allows for the digital archiving of important clinical data, and permits the manufacture of prostheses with improved mechanical properties. These favorable outcomes were achieved by using the patient's existing PMMA complete denture as a custom tray for a final impression with light-bodied Polyvinylsiloxane. Subsequently, the resulting models were digitized, and a digital complete denture was designed and manufactured in an expedited manner using CAD-CAM techniques. Therefore, this case report highlights the potential of CAD/CAM technology to predictably restabilize oral functions and improve patients' quality of life.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.445
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.326
Teacher spread0.306 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMedicinaSame topicDental materials and restorationsFrench-language works237,207