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Record W2333550037 · doi:10.1097/prs.0000000000000679

Local Anesthetics

2014· article· en· W2333550037 on OpenAlexaff
Donald H. Lalonde, Alison Wong

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2014
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsSaint John Regional HospitalDalhousie University
Fundersnot available
KeywordsMedicineLocal anesthesiaLocal anestheticAnesthesiaCannulaSedationPain controlSurgery

Abstract

fetched live from OpenAlex

SUMMARY: Local anesthesia in plastic surgery is undergoing a revolution. In the last 10 years, significant improvements in technique have permitted surgeons to do more and more under pure local anesthesia to increase patient safety and convenience while maintaining total patient comfort during the injection of the local anesthesia and while the procedure is accomplished. Many procedures which used to require sedation are now being performed without it. This article explores some of the new advances in local anesthesia such as painless blunt-tipped cannula local anesthetic infiltration, decreased pain with sharp needle tip injection, and long-lasting local anesthetics with delayed release from liposomal encapsulation. This article also examines the best evidence of the last 10 years of advances of pain control with local anesthesia.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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