Bibliographic record
Abstract
Nearly half a century ago, Lowell T. Coggeshall recommended, through what has come to be known as the Coggeshall Report, that physician education-medical school (or undergraduate medical education [UME]), residency training (or graduate medical education [GME]), and continuing medical education (CME)-be "planned and provided as a continuum." While the dream of a true continuum remains unfulfilled, recent innovations focused on defining and assessing meaningful outcomes at last offer the anchor for the creation of a seamless, flexible, and ongoing pathway for the preparation of physicians. Recent innovations, including a widely accepted competency framework and entrustable professional activities (EPAs), provide key tools for creating a continuum. The competency framework is being leveraged in UME, GME, and CME and is serving as the foundation for the continuum. Learners and those who assess them are increasingly relying on observable behaviors (e.g., EPAs) to determine progress. The GME community in the United States and Canada has played-and continues to play-a leading role in the creation of these tools and a true medical education continuum. Despite some systemic challenges to implementation (e.g., premedical learner formation, time-in-step requirements), the GME community is already operationalizing these tools as a basis for other innovations that are improving transitions across the continuum (e.g., competency-based progression of residents). The medical education community's greatest responsibility in the years ahead will be to build on these efforts in GME-joining together to learn from one another and develop a continuum that serves the public and the profession.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.403 | 0.240 |
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".