Connecting Young Minds (CYM) 2024 Undergraduate Research Conference: 5-Minute Scientific Research Presentations
Bibliographic record
Abstract
Connecting Young Minds (CYM) is a bilingual research conference at the University of Ottawa, created and run by students to enrich the experiences of undergraduates in Science, Technology, Engineering, and Mathematics (STEM). With a mission to inspire research interest and foster innovation, CYM offers students a unique platform to present their research to an audience and expert judges. Every year, the conference hosts a research competition where students submit abstracts or proposals. Selected candidates present their work in a five-minute session, followed by a Question & Answer period, with three grand winners chosen on the conference day. Additionally, students engage with industry professionals, keynote speakers, and past uOttawa valedictorians through presentations and networking sessions. Originally started within the Faculty of Science, CYM has expanded to reach all STEM faculties. With over 300,000 students engaged on social media, 1,000 new followers, and over 300 attendees, CYM is now uOttawa’s largest STEM conference. As the university's only bilingual undergraduate research conference, CYM connects anglophone and francophone students with bilingual, world-renowned researchers, providing an exceptional platform for undergraduates to explore STEM fields and contribute to innovative research in a collaborative environment. Abstracts in this booklet were submitted by participants on a volunteer basis.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.251 | 0.092 |
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".