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Record W7095486473

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2016· article· en· W7095486473 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipCareer planningPlan (archaeology)MEDLINEResidency training
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT • RÉSUMÉ Background: There has been little investigation into the attitudes and aspirations of current ophthalmology residents.The object of this study was to investigate the factors influencing career choice and to identify the future plans of Canadian ophthalmology residents. Methods: All ophthalmology residents in English Canadian ophthalmology residency training programs were invited to complete an anonymous survey in June 2006. Data were categorized by demographic variables and basic statistics; χ2 comparative analyses were performed. Results: Of 128 residents surveyed,49 (38%) responded to the survey.Having the ability to combine medicine and surgery was the most common factor influencing the decision to pursue ophthalmology (98 % of respondents), with intellectual stimulation (76%) and mentorship (50%) also emerging as important factors.The majority of residents (62%) plan on pursuing fellowship training, with medical retina, anterior segment/cataract, and cornea being the most popular choices (36%, 34%, and 32%, respectively). Most residents expressed plans of pursuing fellowships abroad, and only 22 % planned on training within Canada. Fourteen percent indicated an interest in performing laser refractive surgery, female residents being significantly less likely than males to express such an interest (0 % vs. 21%; p < 0.02). Most residents (71%) expressed the wish to practice in an urban or suburban

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.004

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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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