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Record W2335209736 · doi:10.1097/prs.0b013e318208d2c8

Trends in Level of Evidence in Facial Plastic Surgery Research

2010· article· en· W2335209736 on OpenAlexaff
Caroline Xu, David W. J. Côté, Raiyan H. Chowdhury, Andrew T Morrissey, Khalid Ansari

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicinePlastic surgeryOtorhinolaryngologyEvidence-based medicineConfidence intervalReconstructive surgeryHead and neckHead and neck surgerySurgeryGeneral surgeryAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence-based medicine has increasingly become an integral part of clinical research and practice. The purpose of this study was to assess the trends in the level of evidence in leading facial plastic surgery journals in recent years. METHODS: All scientific articles within the field of facial plastic surgery published in The Laryngoscope, Archives of Facial Plastic Surgery, Otolaryngology-Head and Neck Surgery, Journal of Plastic Surgery, and Plastic and Reconstructive Surgery from 1999, 2002, 2005, and 2008 were rated for level of evidence. The presence of p values and confidence intervals was also noted. RESULTS: Of 975 articles reviewed, 88 percent were clinical and 88 percent were therapy articles. Overall, there was an increase in the average level of evidence of articles published from 1999 to 2008. There was also a significant increase in the proportion of articles reporting p values and confidence intervals. However, the number of articles containing level 1 or 2 evidence remains low. CONCLUSIONS: With the increased demand for evidence-based medicine, facial plastic surgery literature has seen an overall increase in the quantity of higher level evidence research published. However, articles representing level 1 and 2 evidence remain rare.

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)0.168
metaresearch head score (Gemma)0.583
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1680.583
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0080.008
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.910
GPT teacher head0.553
Teacher spread0.357 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2010
Admission routes1
Has abstractyes

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