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Record W4399437936 · doi:10.21037/fomm-23-11

Using zinc oxide-based temporary materials as contrast methods: a practical and simple approach for planning prosthetically driven sinus elevation

2024· article· en· W4399437936 on OpenAlexaff
Francisco X. Azpiazu-Flores, Damian J. Lee

Bibliographic record

VenueFrontiers of Oral and Maxillofacial Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsElevation (ballistics)ZincSimple (philosophy)Contrast (vision)Computer scienceMaterials scienceMetallurgyEngineeringStructural engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract: Endosteal implants are a well-established treatment modality to rehabilitate partially and completely edentulous patients. Contemporary regenerative materials and surgical techniques such as direct sinus elevation permit placing endosteal implants predictably in ridges with severe vertical deficiencies. One of the biggest challenges related to this augmentation procedure occurs during the planning stage, when the access to the maxillary sinus, and the number of implants required are tailored specifically for the clinical situation. To minimize the morbidity and maximize post-surgical recovery the extension of lateral window must correspond with the planned implant positions and should not be extended beyond. When establishing these positions, the dentist in charge of the planning the case must be able to clearly visualize the proposed contours of the restorations, their long axes, and their relationship with the residual ridge and the underlying maxillary sinus anatomy. Traditionally, radiographic templates involving contrast agents such as barium sulfate, and tin foil have been used for this purpose; however, the use of these materials often involves extensive dental laboratory procedures. This brief report presents an alternative use for zinc-oxide-based dental materials that permits visualizing the desired prosthetic contours at the diagnostic stage and ensures the placement of the graft material in prosthetically favorable positions.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.391
Teacher spread0.316 · 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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