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Cutaneous Vasculature of the Forearm

2003· article· en· W2000802649 on OpenAlexaff
George W. Kanellakos, Daping Yang, Steven F. Morris

Bibliographic record

VenueAnnals of Plastic Surgery · 2003
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsForearmMedicineAnatomyCadaver

Abstract

fetched live from OpenAlex

In Brief Five fresh human cadavers were injected with lead oxide, gelatin, and water. Nine forearms were dissected and an overall map of the cutaneous vasculature by source vessel was constructed. The average number of arterial perforators per source vessel was calculated. The forearm was then divided into three regions, and the density of perforators per region was calculated and compared. The overall number of arterial perforators decreases from proximal to distal in the forearm, but the overall density of perforators 0.5 mm or larger remains uniform. It was observed that the distal third of the forearm has a rich supply of smaller caliber arterial perforators compared with the proximal two-thirds of the forearm. The angiographic studies demonstrate a series of arterial perforators arising from the radial and ulnar arteries. The perforators in turn are linked longitudinally with other perforators from the same source vessel and transversely with the other major vessel. An understanding of this pattern of arterial supply of the forearm integument is helpful for the design of pedicled skin flaps and perforator flaps in the forearm. Five injected fresh forearm cadaver dissections demonstrated a decreasing density of linked arterial perforators from proximal to distal. However, the distal third of the forearm was found to have a richer supply of smaller-caliber arterial perforators.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.039
GPT teacher head0.276
Teacher spread0.237 · 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

Citations25
Published2003
Admission routes1
Has abstractyes

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