MétaCan
Menu
Back to cohort
Record W2018305892 · doi:10.1177/155335060501200410

The Steinberg-Bernstein Centre for Minimally Invasive Surgery at McGill University

2005· article· en· W2018305892 on OpenAlex
Gerald M. Fried

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSurgical Innovation · 2005
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineInvasive surgeryGeneral surgerySurgery

Abstract

fetched live from OpenAlex

Surgical skills and simulation centers have been developed in recent years to meet the educational needs of practicing surgeons, residents, and students. The rapid pace of innovation in surgical procedures and technology, as well as the overarching desire to enhance patient safety, have driven the development of simulation technology and new paradigms for surgical education. McGill University has implemented an innovative approach to surgical education in the field of minimally invasive surgery. The goal is to measure surgical performance in the operating room using practical, reliable, and valid metrics, which allow the educational needs of the learner to be established and enable feedback and performance to be tracked over time. The GOALS system and the MISTELS program have been developed to measure operative performance and minimally invasive surgical technical skills in the inanimate skills lab, respectively. The MISTELS laparoscopic simulation-training program has been incorporated as the manual skills education and evaluation component of the Fundamentals of Laparoscopic Surgery program distributed by the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and the American College of Surgeons.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.045
GPT teacher head0.277
Teacher spread0.232 · 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