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Record W2589829191 · doi:10.1177/2513826x1600200208

The Use of Free Tissue Transfer with An Anterolateral Thigh Flap for the Treatment of Large Keloids On the Head and Neck

2016· article· en· W2589829191 on OpenAlexaffvenue
Aaron C. Van Slyke, Nicholas Carr, Andrew Hodges

Bibliographic record

VenuePlastic Surgery Case Studies · 2016
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineKeloidHead and neckSurgeryThighFree flapSurgical excisionDeformity

Abstract

fetched live from OpenAlex

Keloids are cosmetically, psychologically and functionally debilitating wounds that have proven difficult to treat with surgical excision alone. Large keloids are particularly challenging to treat because many of the current therapies for keloids are unsuitable, and the remaining defect after excision is difficult to close. The authors report a case involving a large disfiguring keloid on the head and neck, which was treated with surgical excision and immediate reconstruction with a free anterolateral thigh fasciocutaneous flap. No further adjuvant therapy was undertaken. At one-year follow-up, there was no recurrence at the recipient site, and the donor site healed without deformity. The free fasciocutaneous anterolateral thigh flap may be effective at treating large keloids in the head and neck region; however, well-controlled clinical studies are needed to establish this.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.244

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)0.0000.000

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 head0.112
GPT teacher head0.345
Teacher spread0.233 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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