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Record W2012897585 · doi:10.1007/s00268-013-2414-x

Surgical Resident Experience in Breast Disease: A National Study

2014· article· en· W2012897585 on OpenAlexaffabout
Tulin Cil, Frances C. Wright, Claire Holloway

Bibliographic record

VenueWorld Journal of Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreThe Wilson CentreWomen's College HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCompetence (human resources)Breast surgeryVascular surgeryGeneral surgeryBreast diseaseDiseaseMastectomyCardiothoracic surgeryFamily medicineSurgeryBreast cancerCardiac surgeryInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Management of breast disease is an integral component of general surgery. This study was performed to describe the exposure to breast disease by residents in Canadian general surgery programs. METHODS: This study involved a 20-item survey and pilot semistructured interviews. Surgical trainees at 12 training programs in Canada participated in the survey. Results were used to characterize resident experience with breast surgery and clinics. RESULTS: Residents across all post-graduate training years and from 12 Canadian medical schools responded (n = 162, 44 %). Residents had the most breast surgery experience in PGY2 and PGY3 years. One third of trainees performed ≤ 1 breast procedure per month. Only 25 % had attended more than one breast clinic per month. Lumpectomies were the most common procedure (20.7/year) and 94 % of residents performed sentinel lymph node biopsy. Four pilot semistructured interviews were performed. The greatest stated barriers to breast training were "lack of time" and the impression that these were "lower priority cases." CONCLUSIONS: Achieving competence in breast disease management is a key requirement for general surgery trainees. Surgical educators must ensure that the quality and quantity of residency training in breast diseases is sufficient for future surgeons to provide optimal patient care.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.075
GPT teacher head0.355
Teacher spread0.280 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

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