Examination Outcomes Following Use of Card Games for Learning Radiographic Image Quality in Veterinary Medicine
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
Understanding the concepts of radiographic image quality and artifact formation can be difficult for veterinary students. Two educational card games were previously developed to help students learn about factors affecting contrast and blackness as well as radiographic artifacts. Second-year veterinary students played one of the two card games as a part of their normal studies for their veterinary imaging course and later took the radiographic physics quiz normally administered during the course. Performance on quiz questions related to each of the two games was compared between students who played each respective game and those who did not. The hypothesis was that students who played a game would perform better on related questions than those who did not play that game. For the contrast and blackness questions, students who played the associated game as part of their studies performed better than those who only studied by conventional means (mean 4.3 vs. 3.8 out of 5 points, p=.02). However, there was no significant difference in results between groups for artifacts questions (mean 4.7 vs. 4.5 out of 5 points, p=.35). Based on these results, educational game play can have benefits to student learning, but performance may be dependent on specific game objectives and play mechanics.
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 | 0.009 | 0.026 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it