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Record W2031989238 · doi:10.1002/micr.20410

Application of three‐dimensional digitalized reconstruction of an anterolateral thigh flap and an arterial dorsalis pedis flap

2007· article· en· W2031989238 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrosurgery · 2007
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineMicrosurgeryAnatomy3D reconstructionCadaver3d modelSurgeryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Developments in the field of digitalized technique and three-dimensional (3D) reconstruction methods allowed a precise description of anatomy structures. With the development of Visible Human Project (1989) and Virtual Chinese Human (VCH) techniques, we could get more precise anatomic images. Digitized visible models of these structures can be a useful tool in clinical training. Combining modern radiology and VCH techniques, we designed a method to establish digitized visible models of anterolateral thigh (ALT) flap and arteria dorsalis pedis (ADP) flap from adult fresh cadaver specimens perfused with lead oxide-gelatine mixture and VCH Male III dataset. The 3D reconstructed visible models established from these datasets perfectly displayed the anatomic structures of ALT flap and ADP flap. This is the first report on the ACFL and ADP structures which were reconstructed digitally.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.380

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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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