Surgery 101 Podcast: Episodes 21–30
Bibliographic record
Abstract
Abstract This resource is a series of podcasts intended to serve as brief introductions to and reviews of surgical topics for medical students. Each topic is covered in 15–20 minutes so that learners can quickly grasp the basic concepts relating to a common surgical problem. Learning objectives are provided for each topic; episodes are divided into chapters and conclude with several key points to summarize the topic. Topics covered in this module include pyloric stenosis, surgery of the spleen, postoperative complications, heart transplantation, liver transplantation, pancreatic cancer, aortic dissection, coronary artery bypass grafting, pediatric antenatal hydronephrosis and vesicoureteral reflux, and pediatric incontinence and infection. We recommend that episodes be provided to students before a seminar to allow them to quickly get to grips with basic information on a topic. This way, the time in face-to-face teaching can be spent applying knowledge to specific clinical scenarios. Our students also report listening to podcasts during dedicated study time, while reviewing before an examination, while on call, and while travelling or exercising. We have also used the podcasts within a seminar format, with students and presenters listening to the podcast together and discussing the topics raised. Surgery 101 has been produced since October 2008; it was created by Dr. Parveen Boora and Dr. Jonathan White and is currently produced by the Undergrad Surgery Mobile Podcasting Studio Team with the assistance of the members of the Surgery Department at the University of Alberta.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 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; both teacher heads agree on what is shown here.
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".