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Record W4308136677 · doi:10.1177/07488068221127831

Comparisons of Outcomes of Chin Implantation Using the Transoral Versus Submental Technique: A Systematic Review

2022· review· en· W4308136677 on OpenAlex
Corliss Best, Brittany Best, Ji Yun Choi, Jonathan M. Sykes, Hedyeh Javidnia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe American Journal of Cosmetic Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsNOSM UniversityUniversity of Ottawa
Fundersnot available
KeywordsChinMedicineComplicationCochrane LibrarySurgeryMEDLINESystematic reviewSignificant differenceDentistryRandomized controlled trialInternal medicine

Abstract

fetched live from OpenAlex

Background: Chin implantation is a commonly performed facial plastic surgery procedure. There are 2 approaches to this procedure: submental and transoral. There is no consensus as to which is the best and safest approach. Objective: The objective of this review is to ascertain the risks and benefits of using an intraoral versus submental approach for chin implantation. Methods: A systematic review of all articles published in MEDLINE, Embase, Cochrane Library, and Google Scholar was performed from 1966 to 2020. Results: A total of 1410 articles were reviewed and 38 were chosen for the review based on predetermined selection criteria. Total complication rates in the transoral group ranged from 0% to 14.7%, whereas total complication rates in the submental group ranged from 0% to 15%. No clear difference in the rates of any specific complication was found between the 2 groups. Conclusion: There is no demonstrated difference in complication rates between the 2 approaches to chin implantation. Individual patient assessment and surgeon preference remain the most important determinants of surgical approach.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.354
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.128
GPT teacher head0.410
Teacher spread0.282 · 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