The 15th Annual University of Ottawa Healthcare Symposium: 2024 Pitch-O-Rama Competition
Bibliographic record
Abstract
The University of Ottawa Healthcare Symposium (UOHS) is a one-day undergraduate health conference aiming to increase awareness of the interdisciplinary field of health. Initially created by undergraduate students fourteen years ago, UOHS has grown to become the University of Ottawa’s largest healthcare conference with the goal of providing students with a holistic view of healthcare, fostering networking opportunities and encouraging the exploration of novel health disciplines to support their professional endeavors. The 2024 UOHS conference was held on January 27th, 2024, at 55 Laurier Avenue East in Ottawa. This year's conference theme, iHealthcare, aimed to prompt attendees to reflect on the transformative impact of technological innovations on patient care, diagnostics, and healthcare delivery. As a cherished tradition, the 2024 UOHS conference hosted Pitch-O-Rama, an Elevator Pitch Competition blending creativity with research innovation. Participants crafted and orally presented innovative research abstracts using slideshows. Participants were judged by a specially invited panel based on clarity, engagement, relevance to society, solving a knowledge gap worth funding, and creativity in presentation. This book will showcase the works of the winners and honorable mentions of the 2024 Pitch-O-Rama competition. For additional details about UOHS, please visit UOHS’s website: https://www.uohs-csuo.com/.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.198 | 0.068 |
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".