A Comparison of Commercial Anatomy Educational Software
Bibliographic record
Abstract
An online version of an existing undergraduate, systemic human anatomy course is under development. To accommodate the laboratory component of the online section, commercially available anatomy educational software will be used to demonstrate 3D structures via application sharing within a virtual classroom. Eleven anatomy software programs were reviewed to determine their suitability, on the basis of: quality of digital models (resolution, comprehensiveness of anatomical structures and labels, inclusion of cross sectional anatomy), volumetric data used to create models, manipulation of models (virtual dissection, rotational axes, vantage points, rendering speed), program functionality (saving and sharing dissections, querying for structures, ease of use of the menu) and cost. The software we reviewed will not meet all of our online teaching needs. No program was found to have sufficient anatomical detail and visual clarity of digital models for the central nervous system (CNS). Supplementary online materials for the CNS component of the course will be developed to use in conjunction with one of the eleven existing software packages. Grant Funding Source : Departmental Funding
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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 | 0.017 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".