Connecting Young Minds (CYM) 2023 Undergraduate Research Conference: 5-Minute Scientific Research Presentations
Bibliographic record
Abstract
Connecting Young Minds (CYM) is a bilingual research conference created and run by students at the University of Ottawa. Our mission is to enrich the undergraduate experiences of STEM students by providing a vessel to inspire interest in research, paving the way for brighter futures and innovative minds. The conference allows students to present or propose their research to an audience and a panel of judges, to gain experience drafting scientific literature, and the chance to network with industry professionals and past valedictorians from the University of Ottawa. Each year, CYM hosts an undergraduate-level research competition in which participants submit an abstract or a proposal on their research. Top candidates are selected by a panel of professional scientists to further compete at the conference, where they are given five minutes to present their research followed by a Question & Answer period. Oral presentations are also judged by professional scientists and three grand winners are selected on the conference day. Additionally, the CYM Conference engages the interests of students in STEM programs through presentations and networking sessions held by keynote speakers. 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 | 0.003 | 0.006 |
| 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 | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.261 | 0.110 |
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".