Surgery 101 Podcast: Episodes 31–40
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
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 around 15 minutes long so that learners can quickly grasp the basic concepts relating to a common surgical problem. Learning objectives are provided for each episode; episodes are divided into chapters and conclude with several key points to summarize the topic. The topics in this module cover coma, subarachnoid hemorrhage, intracerebral hemorrhage, carotid stenosis, otolaryngology, diverticular disease, periampullary and pancreatic cancers, rectal cancer basics, missed appendicitis, and compartment syndrome. 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. 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. That way, time in face-to-face teaching can be spent applying knowledge to specific clinical scenarios. Students can also listen to the 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.
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 | 0.001 | 0.004 |
| 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) | 0.003 | 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 it