Navigating Your First Cut: A Hands‐off Animated Guide to the First Year Anatomy Lab
Bibliographic record
Abstract
Knowledge of gross anatomy is a critical component of a medical student's education. An understanding of human anatomy is equally essential for the practicing clinician. Historically, schools have solely used cadaver dissections to teach the anatomical sciences. However, lab sessions can be overwhelming, in particular the first session. Students in their first year of medical school are confronted with so many unknowns, and they struggle to prepare mentally and academically for the experience. Where do you cut? What is underneath, beside, above, or below what you are cutting? What are you looking for? A learner, who is yet unfamiliar with the terms, may find written instructions for the dissection difficult to understand. So how does one enhance learning of gross anatomy? In recent years, many medical schools have supplemented cadaver dissections with multimedia, where as others have completely replaced cadaver dissections with prosections or multimedia. We pursued the former method to improve learning: creating an animated video guide for the first gross anatomy dissection in the first year medical undergraduate curriculum. The video takes the learners through the technical and academic steps of their first dissection. And for many students, the video was their first real look at what dissection looks and sounds like. The aim was to alleviate some of the anxieties as students enter this transformative component of their education. We surveyed the students before and after they completed the lab to understand whether the video was helpful. An overwhelming majority of respondents rated the video as very helpful in preparing them for this experience. Some of the comments included: “It was really helpful to see a cadaver being cut before having to do [the dissection] to help mentally prepare” and “The video could not have prepared me better”. In addition, nearly all respondents said they would like to see more videos in the future. Given its reception, we conclude that this visual guide served to optimize the students' gross anatomy experience, and thus their learning and understanding of the material.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".