Bibliographic record
Abstract
The 2025 PUGS Case Competition is the first-ever research case competition organized by the Physiology and Pharmacology Undergraduate Society (PUGS) at Western University. This competition served as an opportunity for competitors to gain critical research analysis skills. Teams of two to four undergraduates were paired with a graduate student mentor and presented a novel research proposal that aligned with the competition’s theme: Age-Related Diseases (ARD). The competition spanned from March 14, 2025 to March 24, 2025, culminating in a case competition day, where top teams presented their solutions. Abstracts and presentations explored innovative approaches to diagnosing or treating an ARD of choice, which may include modifying existing disease treatment or incorporating a novel component to overcome its shortcomings. Over 100 participants submitted abstracts proposing solutions across interdisciplinary fields, including Physiology and Pharmacology, Synthetic Biology, Pathology, Health Sciences, Biochemistry, Microbiology and Immunology, Molecular Biology and Genetics, and Artificial Intelligence. The top 50% of winning submissions are featured in this conference abstract booklet, with the top six teams delivering additional oral presentations. Awards were presented to the top three teams. Abstract and presentation scoring was facilitated by a panel of faculty judges from the Department of Physiology and Pharmacology.
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.
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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.220 | 0.063 |
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".