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The Subscapular Arterial Tree as a Source of Microvascular Arterial Grafts

2004· article· en· W2331022250 on OpenAlexaff
S Valnícek, Matthew Mosher, Jason K. Hopkins

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of SaskatchewanKelowna General Hospital
Fundersnot available
KeywordsArterial treeMedicineCadaverArteryAnatomyForearmArterial bloodArterial dissectionDissection (medical)SurgeryCardiologyInternal medicine

Abstract

fetched live from OpenAlex

The subscapular arterial tree may be used as a source of microvascular grafts to replace damaged or diseased portions of arteries, particularly in the hand and forearm. By studying cadaver dissections, it is possible to estimate the number of branches that may be found at different arterial segment lengths from the origin of the subscapular artery. Fifty-five preserved cadaver subscapular arterial trees were dissected, and the branching patterns were documented. Three major arterial branching patterns of the subscapular artery were observed with one, two, and three major branches to the serratus anterior in 60 percent, 29 percent, and 9 percent of the cases, respectively. The authors determined the number of 1-mm-diameter, 1-cm-long branches arising from each of six 3-cm regions of the arterial tree measured from the origin of the subscapular artery to the end of the longest terminal branch. The probability of finding at least one usable terminal branch that is at least 12.0 cm in length was found to be 98 percent. Typically, there are two to five useful branches at this distance. Such information may help surgeons fine tune their process of selecting an appropriate arterial donor site for a particular arterial defect and supports the use of the subscapular arterial tree as a donor site for microvascular arterial grafts.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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 designBench or experimental
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

Citations35
Published2004
Admission routes1
Has abstractyes

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