Bibliographic record
Abstract
Candidates included: • Dr. Judith Hall, a pioneering doctor in pediatrics and genetics, and a UBC Professor Emerita; • Raul Pacheco-Vega, an instructor in UBC’s Department of Political Science and a prominent social media maven; • Michael V. Smith, an interdisciplinary artist and Assistant Professor of Creative Writing in the Faculty of Creative and Critical Studies at UBC Okanagan; • David Watmough, a long-established B.C. writer, playwright, short-story writer, critic and broadcaster; • Joanne Ursino, a member of UBC’s Equity Office, an active member of Vancouver’s queer community and an artisan; • Andrew “Chima”Akomas, who was born in Winnipeg, Manitoba but grew up in Nigeria. He returned to Canada in 2003 and is majoring in commerce at UBC. Akomas was diagnosed with Marfan syndrome, a genetic disorder of the connective tissue. After returning to Canada, he also began to lose his sight and has been blind for three years; • Alyas Omeed, a human rights and disability activist from Afghanistan who is attending UBC (he is improving his language skills and then plans to start his Bachelor of Arts program). He lost his sight as a child during Afghanistan’s civil war; • Rimple Cheema and Lisa Sun, UBC students and participants in the Social Entrepreneurship 101 (SE101) program at the Sauder School of Business; • Darrell Bailie, a reference librarian at UBC’s Koerner Library, and an extreme athlete and traveller.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.024 | 0.033 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.282 | 0.087 |
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".