MétaCan
Menu
Back to cohort
Record W2016850464 · doi:10.1177/1538574407299800

Totally Laparoscopic Aortic Surgery: Comparison of the Apron and Retrocolic Techniques in a Porcine Model

2007· article· en· W2016850464 on OpenAlex
Stéphane Elkouri, Nathalie Beaudoin, Luc Bruneau, Cathie Guimond, Véronique Daniel, Jean-François Blair

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

VenueVascular and Endovascular Surgery · 2007
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineAnastomosisSurgeryLaparoscopyDissection (medical)Laparoscopic surgeryArteriotomyArtery

Abstract

fetched live from OpenAlex

This study evaluated the learning curve for a second-year general surgery resident and compared 2 totally laparoscopic aortic surgery techniques in 10 pigs: the transretroperitoneal apron approach and the transperitoneal retrocolic approach. Five end points were compared: success rate, percentage of conversion, time required, laparoscopic anastomosis quality, and learning curve. The first 3 interventions required an open conversion. The last 7 were done without complications. Mean dissection time was significantly higher with the apron approach compared with the retrocolic approach. The total times for operation, clamping, and arteriotomy time were similar. All laparoscopic anastomoses were patent and without stenosis. The initial learning curve for laparoscopic anastomosis was relatively short for a second-year surgery resident. Both techniques resulted in satisfactory exposure of the aorta and similar mean operative and clamping time. Training on an ex vivo laparoscopic box trainer and on an animal model seems to be complementary to decrease laparoscopic anastomosis completion time.

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)0.002
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 score0.015
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.278
Teacher spread0.255 · 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