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Record W2315604032 · doi:10.1902/jop.2016.150512

Usage of Bone Replacement Grafts in Periodontics and Oral Implantology and Their Current Levels of Clinical Evidence — A Systematic Assessment

2016· review· en· W2315604032 on OpenAlexaff
Daliah Salem, Zuhair S. Natto, Satheesh Elangovan, Nadeem Y. Karimbux

Bibliographic record

VenueJournal of Periodontology · 2016
Typereview
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsPeriodontologyMedicineDentistryMEDLINEPeriodontitisCochrane LibraryMeta-analysisPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this review is to evaluate the levels of clinical evidence for bone replacement grafts available in the United States for periodontics and oral implantology purposes. METHODS: A search was performed using PubMed, the Cochrane Library, and Google Scholar for articles relating to the use of bone replacement grafts in implant and/or periodontics by two independent reviewers. Articles unrelated to the topic, not involving patients, not including abstracts, or in languages other than English were excluded. Selected articles were graded according to "levels of evidence" based on guidelines originally introduced by Wright et al. (2003). RESULTS: There was limited published peer-reviewed clinical literature available regarding US commercially available bone replacement grafts in periodontics and oral implantology. Of 144 bone replacement grafts available in the United States according to Avila-Ortiz et al. (2013), only 52 met the inclusion criteria. The majority of materials used were allografts (26 of 93 available in the United States), followed by alloplasts (15 of 30) and xenografts (11 of 21). CONCLUSION: Dental providers should be aware of the limited evidence that qualified for a strong rating supporting the clinical efficacy of these materials for periodontics and oral implantology purposes using the inclusion criteria selected in this study.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.214
GPT teacher head0.503
Teacher spread0.289 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations18
Published2016
Admission routes1
Has abstractyes

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