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Record W1488321798 · doi:10.1111/cid.12186

In Vivo Evaluation of Two‐Piece Implants Placed Following One‐Stage and Two‐Stage Surgical Protocol in Posterior Mandibular Region. Assessment of Alterations in Crestal Bone Level

2013· article· en· W1488321798 on OpenAlexvenueno aff
Minkle Gulati, Vivek Govila, Sunil Verma, Balakrishnan Rajkumar, Vishal Anand, Anuj Aggarwal, Nikil Jain

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2013
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersCore Research for Evolutional Science and Technology
KeywordsMedicineStage (stratigraphy)DentistryImplantOrthodonticsProtocol (science)Surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Endosseous implants can be placed following either two-stage technique requiring second-stage surgery or one-stage technique, which does not involve a second surgical intervention. PURPOSE: The present study was undertaken to evaluate and compare the changes in crestal bone level when two-piece implants were placed in posterior mandibular region following one-stage and two-stage surgical protocol. MATERIALS AND METHODS: A parallel group randomized prospective study was designed in which 20 two-piece implants were placed in the posterior mandibular region of 16 partially edentulous healthy patients following either one-stage (Group I) or a two-stage surgical protocol (Group II). Alterations in crestal bone level were assessed with the help of DentaScan at baseline, that is, at the time of implant placement, third month and sixth month. RESULTS: Nonsignificant differences were seen in both groups in terms of changes in crestal bone level at the final evaluation. CONCLUSIONS: Hence, it could be concluded that two-piece implants can be placed following one-stage surgical protocol as predictably as when two-stage surgical technique is followed.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.243
GPT teacher head0.543
Teacher spread0.300 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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