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Record W2001812515 · doi:10.1563/0.824.1

Preserving the Socket Dimensions With Bone Grafting in Single Sites: An Esthetic Surgical Approach When Planning Delayed Implant Placement

2007· article· en· W2001812515 on OpenAlexaff
Tassos Irinakis, Moe Tabesh

Bibliographic record

VenueJournal of Oral Implantology · 2007
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAlveolar ridgeDentistryImplantMedicineBone graftingDental alveolusSoft tissueOrthodonticsComputer scienceSurgery

Abstract

fetched live from OpenAlex

Recent advancements in barrier membranes, bone grafting substitutes, and surgical techniques have led to a predictable arsenal of treatment methods for clinicians who practice implant dentistry. The contemporary clinician is supplied with proven knowledge, substantiated materials, and instrument inventory that allows implant placement in cases that used to be reserved for the specialist in the past because of their complexity. Nowadays, postextraction alveolar ridge maintenance can be a predictable procedure and can certainly aid the clinician in preventing ridge collapse, thereby allowing for implant placement in a position that satisfies esthetics and function. Extraction socket maintenance for future implant therapy does not rule out immediate implant placement but rather provides an additional option when treatment planning implant patients. This article will focus on the concept of extraction socket preservation using regenerative materials. It will describe a technique suggested by the authors to resist bone resorption and soft tissue shrinkage following tooth extraction.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.063
GPT teacher head0.346
Teacher spread0.283 · 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 designObservational
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

Citations49
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of Oral ImplantologySame topicDental Implant Techniques and OutcomesFrench-language works237,207