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Record W2014427412 · doi:10.1097/moo.0b013e32833a2e50

Microvascular reconstruction in the vessel–depleted neck

2010· review· en· W2014427412 on OpenAlexaff
Kevin Wong, Kevin Higgins, Danny Enepekides

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2010
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsMedicineCosmesisNeck dissectionCephalic veinAnastomosisInternal jugular veinSurgeryRadiologyDissection (medical)External jugular veinRadiation therapyVeinCancer

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Microvascular reconstruction for head and neck cancers has improved both cosmesis and functionality of patients undergoing treatment. Many patients have had prior surgery (neck dissection), radiation and/or chemotherapy as part of their management. When microvascular reconstruction is required after previous treatment, finding appropriate vessels for anastomosis can be difficult. In this paper we explore the options for microvascular reconstruction in the vessel-depleted neck. RECENT FINDINGS: Arterial options that exist when the neck is depleted of vessels include the superficial temporal, transverse cervical, thoracoacromial, and the internal mammary artery. Venous options include the cephalic vein and vein grafts. SUMMARY: The external carotid artery and the internal jugular vein are the most commonly utilized vessels in microvascular reconstruction when available. However, prior chemotherapy and/or radiation can cause significant scarring and damage to these vessels. Also in patients who have had previous surgery, these vessels can be resected or altered in a way that they are deemed unusable. In these situations several vascular options exist outside the neck.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.098
GPT teacher head0.382
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations54
Published2010
Admission routes1
Has abstractyes

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