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Record W29518688

Current issues of interventional radiology in Canada: a national survey by the Canadian Interventional Radiology Association.

2005· article· en· W29518688 on OpenAlexaffabout
Mark O. Baerlocher, Murray Asch, Eran Hayeems

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineInterventional radiologyPaceDemographicsRadiologyMedical physics
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine current issues facing the field of interventional radiology (IR) in Canada. METHODS: An anonymous online survey was emailed to all members of the Canadian Interventional Radiology Association. The survey was open for 1 month. RESULTS: A total of 83 survey responses were received (of an estimated possible 233). Responses regarding demographics, aspects of practice, research, and IR trainee education were collected. CONCLUSIONS: Several issues were identified as pertinent to Canadian interventional radiologists, including a current and future drought of interventional radiologists, a lack of women in the profession, inadequate protected research time for those in academic practice, a lack of protected clinical time, concern regarding turf issues with other specialties, division between interventional and diagnostic radiology, and the ideal profile of the future interventional radiologist. The field of interventional radiology (IR) continues to develop, expand, and mature at a rapid pace. As the field is still relatively young, several issues are bound to arise. It is important therefore to stay abreast of the current trends and opinions of practitioners within the field.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.153
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.055
GPT teacher head0.324
Teacher spread0.269 · 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 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

Citations14
Published2005
Admission routes2
Has abstractyes

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