UBC 2022 Multidisciplinary Undergraduate Research Conference: Inspire Change
Bibliographic record
Abstract
The Multidisciplinary Undergraduate Research Conference (MURC) is a conference for undergraduate students at the University of British Columbia (UBC) to showcase their research in front of their fellow UBC students, family, and friends. Researchers may choose one of three formats to showcase their research: oral presentation, poster, or virtual presentation. Presentations are categorized into four multidisciplinary themes: Health and Wellness; Individual, Community and Society; Sustainability and Conservation; and Innovation and Technology. Presentations were evaluated by UBC graduate students and faculty to provide students with feedback on their projects and presentation skills. MURC 2022 was the 19th iteration of the conference and the first ever hybrid (both in-person and virtual) undergraduate research conference held at UBC. The theme for MURC 2022 was Inspire Change. This theme seeks to approach research in a manner that inspires new generations to see that change as an agent of positivity and growth. The in-person components of the conference were held at the UBC Vancouver campus, with poster sessions in the Marine Drive Ballroom and oral presentations in the various lecture rooms in the West Mall Swing Space Building. Virtual presentations were held using the Zoom Meetings videoconferencing software.
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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.086 | 0.020 |
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".