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The Role of the Multimedia Platforms and of Virtual Simulators in Teaching Vascular Laparoscopic Surgery

2005· article· en· W2081521307 on OpenAlexaboutno aff
Albert-Claude Benhamou

Bibliographic record

VenueSurgical Laparoscopy Endoscopy & Percutaneous Techniques · 2005
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVascular surgerySession (web analytics)Laparoscopic surgeryInvasive surgeryEndovascular surgeryGeneral surgeryLaparoscopyMarie curieMedical physicsSurgeryMultimediaCardiac surgeryWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Université Pierre & Marie CURIE & CHU, Paris. This issue of the Journal contains the abstracts of the International Endovascular and Laparoscopic Congress held in Quebec City, Canada, May 20-22, 2004. The reader will find abstracts treating the latest and most significant issues in the field of endovascular surgery, centering particularly on endovascular grafting. The raison d'être of the Congress is to promote the development of laparoscopic vascular surgery. Experts in both fields of minimally invasive vascular surgery presented the latest devices, techniques, and results. The free paper session was of high quality, even taking into account the recent recognition of laparoscopy in vascular surgery. The next Congress, scheduled for May 2006, already promises exciting developments, one of them being the ability to perform an aortic or iliac anastomosis with an automatic device. These devices will be tested clinically during 2005. They are already available for evaluation during laparoscopic vascular hands-on courses (www.vascularlaparoscopy.org). I hope that you will find that these abstracts provide novel information that is helpful in your day-to-day practice. Yves-Marie Dion IELC President

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)0.000
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 score0.531
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.261
Teacher spread0.254 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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