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Bone regeneration at implants placed into extraction sockets of maxillary incisors in dogs

2011· article· en· W1840471565 on OpenAlexaboutno aff
Enzo De Santis, Daniele Botticelli, Fabio Pantani, Flávia Pereira, Marco Beolchini, Niklaus P. Lang

Bibliographic record

VenueClinical Oral Implants Research · 2011
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsBuccal administrationDentistryOsseointegrationDehiscenceMedicineImplantMaxillary central incisorDental alveolusSoft tissueIncisorSurgery

Abstract

fetched live from OpenAlex

AIM: To compare the influence of autologous or deproteinized bovine bone mineral as grafting material on healing of buccal dehiscence defects at implants installed immediately into the maxillary second incisor extraction socket in dogs. MATERIAL AND METHODS: In the maxillary second incisor sockets of 12 Labrador dogs, implants were installed immediately following tooth extraction. A standardized buccal defect was created and autologous bone particles or deproteinized bovine bone mineral were used to fill the defects. A collagen membrane was placed to cover the graft material, and the flaps were sutured to fully submerge the experimental areas. Six animals were sacrificed after 2 months, and six after 4 months of healing. Ground sections were obtained for histological evaluation. RESULTS: After 2 months of healing, all implants were osseointegrated. All buccal dehiscence defects were completely filled after 2 months irrespective of the augmentation material (autologous bone or Bio-Oss(®)) applied. Bone-to-implant contact (BIC) on the denuded implant surfaces was within a normal range of 30-40%. However, the newly formed tissue at 2 months was partially resorbed (>50% of the area measurements) after 4 months. CONCLUSIONS: Applying either autologous bone or deproteinized bovine bone mineral to dehiscences at implants installed immediately into extraction sockets resulted in high degree of regeneration of the defects with satisfactory BIC on the denuded implant surface.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.358
GPT teacher head0.529
Teacher spread0.171 · 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 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

Citations47
Published2011
Admission routes1
Has abstractyes

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