Guía ESC 2019 sobre el tratamiento de pacientes con taquicardia supraventricular
Bibliographic record
Abstract
Research sets the foundation for developing plastic surgeons who think critically and approach clinical practice with an inquisitive mind. The objective of this study was to characterize current attitudes and perceived barriers towards conducting research during residency.A validated 36-item questionnaire was developed by a national task-force of Canadian plastic surgery trainees. The survey was distributed to all 13 plastic surgery programs in Canada. Data was collected for a period of 2 months in the form of multiple choice, Likert scales and short answers.The response rate was 64% (95/149) with representation from all 13 plastic surgery programs across Canada. The top three perceived barriers to conducting research were lack of time (83%), insufficient access to research supervisors and mentors (42%) and the research ethics process (38%). More than 70% of residents were interested in conducting research during residency and 74% of programs have a research requirement integrated into their curriculum. Despite this, less than half of residents (47%) believed that their program fosters a culture that promotes research. This was attributed to multiple factors, including a lack of internal research funding (78%), limited access to a research methods or clinical trials unit (78%), and insufficient research training (68%). University research ranking had no correlation with residents’ scholarly output or their perceptions towards research barriers.Canadian Plastic Surgery residents identified several important factors considered to be barriers to research. Programs can use these findings to address barriers and improve the integration of research throughout residency training.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".