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Record W4297173803 · doi:10.53730/ijhs.v6ns9.12963

Customised abutment for achieving the predictable emergence profile for immediate implant in molar site

2022· article· en· W4297173803 on OpenAlexaff
Ankita Gidwani, Tushar Tanwani, Gaurav Tripathi, Sudeepti Soni, Ankita Srivastava, Juhi Thadlani

Bibliographic record

VenueInternational Journal of Health Sciences · 2022
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsMolarAlveolar ridgeDentistryImplantCoronal planeAbutmentSoft tissueDental alveolusOrthodonticsAlveolar processProcess (computing)Materials scienceMedicineComputer scienceAnatomyEngineeringSurgery

Abstract

fetched live from OpenAlex

The alveolar bone undergoes a remodelling process after tooth extraction, which leads to horizontal and vertical bone loss. These resorption processes complicate dental rehabilitation, particularly in connection with implants. Clinical studies have suggested that retaining roots of hopeless teeth may avoid tissue alterations after tooth extraction. The aim is to seal the surgical site following the outline of extraction socket and to develop an ideal prosthetic emergence profile, modelled on the anatomy of the existing tooth. In present case report a non restorable mandibular molar was treated with socket sealing protocol followed by immediate implant placement. Using sequential osteotomy drills implant site was prepared and roots were dissected in buccolingual direction along the long axis. Roots were extracted using elevators and implant of desired size was placed. A Customized sealing socket abutment (SSA) was prepared to support the coronal emergence profile of the tooth. This technique is a minimally invasive that can preserve the hard and the soft tissue contour of the ridge.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.392
Teacher spread0.348 · 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 designCase report
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

Citations0
Published2022
Admission routes1
Has abstractyes

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