Evaluation of a comprehensive neuroanatomy website in a distributed medical curriculum
Bibliographic record
Abstract
A neuroanatomy website ( www.neuroanatomy.ca ) was created as a resource for all students and as a means of bridging the access to information and specimens gap between all sites in a distributed medical curriculum. The website includes a web atlas with both photos and diagrams, an imaging section with MRI scans, a section with 3D MRI reconstructions, a stroke section and course specific sections such as a weekly quiz. Web 2.0 elements were incorporated such as a wiki and podcasts. A survey was given to the students at the end of the lab block to evaluate the use and usefulness of the website. 85% of students used the website, both at home and during the lab sessions. The sections used primarily were the atlas and the 3D reconstructions. This could be attributable to the uniqueness of the 3D section and the scarcity of prosections to study with. Both the stroke section and the quiz section also showed a good usage by the students. The wiki was poorly received, this might be due to perceived difficulties with the technology or the use of other, preferred means of communication by the class such as online message boards. While most respondents found the website to be a useful tool during the lab sessions (54%), a smaller percentage found the website useful for other curricular objectives in the block (45%). Overall the students rated the website as being a useful learning tool, it was easy to navigate and information was easy to find.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".