Virtual Education in Pediatric Surgery during the COVID-19 Era: Facing and Overcoming Current Challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The novel coronavirus disease 2019 (COVID-19) pandemic has impacted our way of living in an unprecedented manner. Medical professionals at all levels have been forced to adapt to the novel virus. The delivery of surgical services and the subsequent learning opportunities for surgical residents have especially been disrupted and the pediatric surgical community has not been exempted by this. This article highlights the challenges imposed by the pandemic and outlines the various learning modalities that can be implemented to ensure continued learning opportunities throughout the pandemic and beyond. Furthermore, it aims to show how the utilization and expansion of technologies maintain and further increase the communication, as well as the exchange of and access to knowledge among peers. Virtual education-, application-, and simulation-based learning and social media, as well as telemedicine and online conferences, will play a considerable role in the future of surgical specialties and surgical education.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it