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Record W4406749580 · doi:10.53045/jprs.2024-0044

Research on Postoperative Scar Quality of Sutures and Skin Surface Adhesives

2025· article· en· W4406749580 on OpenAlexaboutno aff
Nao Aburakawa, Yuriko Saito, Ayako Higuchi, Keiichiro Iida, Naoko Wada, Makoto Mikami, Satoshi Urushidate

Bibliographic record

VenueJournal of Plastic and Reconstructive Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsnot available
Fundersnot available
KeywordsAdhesiveQuality (philosophy)MedicineSurgeryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Objectives: is established, its use can be expanded for more cases and higher quality medical care can be provided. Methods: and nylon threads, and the time was measured. At the second surgery, all scars were removed, and a histopathological examination was done. Scars were evaluated with the Vancouver Scar Scale (VSS) and visual analogue scale (VAS), and statistical analysis was performed. Results: group. Postoperative VSS scores for pliability were significantly lower in the suture group, and the total VSS score was significantly lower in the suture group from 3 to 6 months postoperatively. Patients rated postoperative wound pain, itching, appearance, and satisfaction with the VAS, but no significant differences were observed between the two groups. The scars were compared with hematoxylin-eosin staining and Elastica van Gieson staining. Differences were seen in the increase of elastic fibers in the dermal reticular layer, a characteristic difference between the two groups. Conclusions: can be further expanded in the future.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.377
Teacher spread0.323 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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