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Record W4221037100 · doi:10.1503/cjs.020719

Guidelines for Canadian bariatric surgical and medical centres: a statement from the Canadian Association of Bariatric Physicians and Surgeons

2022· article· en· W4221037100 on OpenAlexaffvenueabout
Pierre Y. Garneau, Stephen Glazer, Timothy Jackson, Sharadh Sampath, Kenneth L. Reed, Nicolas V. Christou, Joseph Shaban, Laurent Biertho

Bibliographic record

VenueCanadian Journal of Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsMcGill UniversityWindsor Regional HospitalHumber River Regional HospitalGuelph General HospitalUniversité du QuébecMontreal General HospitalWestern UniversityRichmond HospitalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversity Health Network
Fundersnot available
KeywordsMedicineStandardizationMultidisciplinary approachStatement (logic)Medical careFamily medicineSevere obesityObesityWeight lossPathology

Abstract

fetched live from OpenAlex

The goal of this statement is to offer standardization in bariatric care across Canada, to provide patients with optimal access to obesity treatment and potentially improve outcomes by reducing complications, length of hospital stay and readmission rate. The definition of Canadian standards also aims to promote a comprehensive, multidisciplinary approach to patients with obesity, to define the minimal qualifications for surgical and medical training and to offer credentialling for bariatric surgical and medical centres. In addition, we emphasize the importance of developing a national registry for the assessment of quality of care across the country and to evaluate outcomes of long-term treatment. These recommendations are based on expert opinion as well as the most recent clinical evidence.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.276
Teacher spread0.236 · 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.

Study designObservational
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

Citations17
Published2022
Admission routes3
Has abstractyes

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