Evolving anatomy art: a self‐directed learning project (535.2)
Bibliographic record
Abstract
Anatomy education is an integral part of training in medicine and follows a rich narrative of history evolving from ancient study of body systems to present technological approaches of instruction. Similarly, trends to integrate arts and humanities into medical education serve to deepen appreciation of the human condition. The project aims to provide a means of incorporating the arts and humanities into the current undergraduate medical training in the field of anatomy, with the intent of promoting a more holistic method of instruction. Exploration of the history of anatomy though artistic avenues enhances the learning experience of medical students by encouraging personal involvement and individual creativity. An illustration of self‐directed learning of human anatomy and personal reflections by a medical student are presented. The chronological account of the anatomical study of an organ and a body system was briefly depicted in a series of reconstructed sketches and models, with corresponding ruminations of the student artist. Providing an opportunity in anatomy instruction for artistic expression in an analogous manner is beneficial to medical trainees and supplements the existing undergraduate medical curriculum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".