University of Ottawa Healthcare Symposium (UOHS) 2022 Pitch-O-Rama: Undergraduate Elevator Pitch Research Competition
Bibliographic record
Abstract
The University of Ottawa Healthcare Symposium (UOHS) is a one-day undergraduate health conference that aims to increase awareness of the interdisciplinary field of health. This conference engages students’ interest in health through seminars, interactive panel discussions, and a research-based elevator pitch competition. UOHS was created twelve years ago by undergraduate students and has grown to become the University of Ottawa’s largest healthcare conference. Every year, UOHS hosts an event called the Pitch-O-Rama, during one of the conference’s seminar blocks. This event is an elevator pitch competition where individuals have the opportunity to present their healthcare-related research to an audience and panel of judges in a clear and engaging way. The goal of the Pitch-O-Rama is to have students communicate and share their scientific research with the community. The written submissions of the top 3 winners are highlighted in this abstract book. More details about UOHS can be found on our 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.293 | 0.082 |
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".