Effect of the Recently Established Admissions Procedure on Success in the First-Year Exams at the University of Veterinary Medicine Vienna, Austria
Bibliographic record
Abstract
RATIONALE FOR THIS STUDY: The purpose of this study was to compare the success during the first academic year of students who underwent an admissions procedure (class 2005) and students of the three previous classes (2002-2004), who did not undergo an admissions procedure but took their exams under the same curricular framework. METHODOLOGY: Exam results of 802 students of the 2002-2004 classes were compared with those of 181 students from the 2005 class. RESULTS: Students of the 2005 class were more likely to pass all three exams given in the first academic year than students of the 2002-2004 classes (p < 0.001; OR = 3.2), and the quality of two of the three exams (indicated by individual scores) was also significantly better in 2005 than in the preceding classes (p < 0.001). In unselected classes, 25% to 31% of students showed no successful attempts to pass any of the three exams currently administered. CONCLUSION: The implementation of an admissions procedure measuring, among other indicators, academic ability has significantly improved first-year exam performance. Incoming students presenting with higher scores on academic standards are more likely to complete their courses successfully.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".