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Record W2789406210 · doi:10.5826/dpc.0801a05

A new perspective on the nail plate for treatment of ingrown toenail

2018· article· en· W2789406210 on OpenAlexaboutno aff
Jia Tian, Jin Li, Wang Fabin, Zhenbing Chen

Bibliographic record

VenueDermatology Practical & Conceptual · 2018
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNail (fastener)PhalanxAvulsionNail plateSurgerySoft tissueVisual analogue scaleDentistryComplication

Abstract

fetched live from OpenAlex

BACKGROUND: Our routine treatment for ingrown toenail was removal of the surrounding soft tissue and shortening the bone of the distal phalanx. We determined the range and volume of excision based on our experience without an objective standard and routinely performed avulsion of the nail plate. OBJECTIVE: To take the nail plate as an objective mark during surgical treatment of ingrown toenail to ensure accurate excision. PATIENTS AND METHODS: Fifteen patients with ingrown toenails were treated with this technique. We used the lateral borders of the nail plate as a landmark to determine the volume of soft tissue surrounding the nail plate and distal phalanx to be removed. No avulsion of nail plate was performed. RESULTS: No recurrence was observed during the follow-up period, which ranged from 24 to 35 months (29.9 months on average). The visual analog scale for pain showed significant pain relief in the patients. The Vancouver Scar Scale showed acceptable cosmetic outcomes. The width of excised skin ranged from 3.5 to 6.2 mm (5.0 mm on average). CONCLUSION: The use of the lateral borders of the nail plate as a landmark for surgical intervention of ingrown toenail offered excellent outcomes and reduced loss of healthy tissues.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.073
GPT teacher head0.391
Teacher spread0.318 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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