Adapting Nephrology Training Curriculum in the Era of COVID-19
Bibliographic record
Abstract
PURPOSE OF REVIEW: The COVID-19 pandemic has widespread implications not only for clinical practice but also for academic medicine and postgraduate training. The need to promote physical distancing and flexibility within our department has generated important revisions to the core curriculum for the Adult Nephrology Training Program in Vancouver, Canada. SOURCES OF INFORMATION: We reviewed available educational resources and objectives to develop curricular adaptations informed by staff and trainee feedback. METHODS: Many facets of the program including clinical rotations, scholarly activities, evaluation, and wellness have been impacted, and thus revised for online delivery where possible. Trainees have personalized a learning plan based on individual goals and supplemented by a list of internet-based resources for independent review. Changes in learning objectives and methods for specific rotations have occurred and are described. Ongoing evaluation will be undertaken. KEY FINDINGS: Curriculum adaptation in the era of COVID-19 is necessary to ensure ongoing high-quality education for future nephrologists. We describe existing changes to formal training in British Columbia (BC), which will be tailored as the pandemic evolves, and anticipate them to have lasting impact on the way we structure training programs in the future. Standardization and harmonization of modified curriculum may be possible across Canada with sharing of these learnings. LIMITATIONS: Formal evaluation of these changes in terms of knowledge acquisition and examination performance has not yet been undertaken. Next steps will include assessing and documenting the impact of this curricular transformation to further optimize scheduling, educational yield, and trainee wellness.
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 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 | 0.020 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".