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Record W3134023852 · doi:10.21037/atm-20-8074

Peri-implant tissue alteration around tissue-level and bone-level implants in fresh extraction sockets: a histomorphometric study in dogs

2021· article· en· W3134023852 on OpenAlexaboutno aff
Chunan Zhang, Zhao Xu, Shi‐Chong Qiao, Xiaomeng Zhang, Hongchang Lai, Ying‐Xin Gu

Bibliographic record

VenueAnnals of Translational Medicine · 2021
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersShanghai Jiao Tong University
KeywordsAlveolar crestDentistryImplantResorptionMedicineOsseointegrationDental alveolusBone resorptionSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: To compare tissue alteration in fresh extraction sockets between bone-level and tissue-level implants with different neck designs. METHODS: Bilateral premolars of 6 adult Labrador dogs were extracted, and 24 bone-level and tissue-level implants with two different neck designs were immediately placed. At the same time, buccal bony wall thickness in fresh extraction sockets was also recorded. The Straumann® Bone Level (BL) and Standard Plus (SP) implants were positioned at two insertion depths: 1mm below and flush with the alveolar crest. All animals were sacrificed 6 months after the implant placement. Undecalcified block sections were obtained for histological measurement. Vertical bone resorption and biological widths were documented. Statistical analysis consisted of two sample t-test and Wilcoxon sign-rank test. RESULTS: All implants were histologically osseointegrated. There was no significant difference between BL implants and SP implants in vertical bone resorption regardless of the insertion depths (P>0.05). Meanwhile, significant difference was found in lingual biological width between BL (3.16 mm) and SP (2.43 mm) implants when placed 1mm below the alveolar crest (P<0.05). CONCLUSIONS: Within the limits, it seemed that different implant neck designs had little effect on bone remodeling in fresh extraction sockets. However, longer biological width was found in bone-level implants.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.177
GPT teacher head0.420
Teacher spread0.243 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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