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Record W2901365309 · doi:10.1016/j.ejvssr.2018.10.006

Vascular Surgery Fellowships: Comparison of Two Programmes in Canada and the UK

2018· article· en· W2901365309 on OpenAlexaffabout
Wissam Al-Jundi, Mohammed Firdouse, Darren Morrow, Michael G. Wyatt, Mark Wheatcroft

Bibliographic record

VenueEJVES Short Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineVascular surgeryScopusSpecialtyWorkforceMEDLINEGeneral surgerySurgeryFamily medicineCardiac surgeryPolitical science

Abstract

fetched live from OpenAlex

The last decade witnessed the birth of vascular surgery as a standalone specialty. This was accompanied by the rapid development of endovascular techniques, which revolutionised the way vascular diseases are treated. This change in the practice of vascular surgery has had a great impact at all levels, but perhaps none greater than in the training of future vascular surgeons. Hence, there is an increasing demand for a generation of vascular surgeons who are versatile in performing the breadth of vascular and endovascular procedures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.957
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.015
Science and technology studies0.0030.002
Scholarly communication0.0050.002
Open science0.0030.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.023
GPT teacher head0.299
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2018
Admission routes2
Has abstractyes

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Same venueEJVES Short ReportsSame topicAortic aneurysm repair treatmentsFrench-language works237,207