Bibliographic record
Abstract
Editor-in-Chief: Natasha Faroogh Assistant English Editor: Stephanie Settle Assistant French Editor: Gervanne Bourquin Editor of Campus Life: Erika Desjardins Editor of Issues and Ideas: Lindsay Drury Editor of Metropolis: Neya Abdi Editor of Arts and Entertainment: Ashley Moniz Editor of Expressions: Sienna Warecki Communications Officer: Victoria Ramsay Design and Layout: Megan Armstrong Spotted at Glendon Letter from the Editor Vie de Campus Mastermind Club Updates Lumiere concrete de Philippe Blanchard Progress for Music at Glendon Glendon Abroad Tulip Tales! I Want to Ride my Bicycle Issues and Ideas My Battle With Misogyny Keep Warm And Kind This Winter Spirit Week SHOW YOUR #YUSPIRIT Frexpo! Glendon's New Study Space Bienvenue a Notre Nouveau Study Space Ebola in North America Toronto Votes: Tory Beats Doug Ford in race for TO's top job Health and Wellness Strictly Sex The Great Canadian Night Owl Arts and Entertainment Five Guiltiest of Pleasures on the Radio Expressions Snack Attack: A Trio of Tasty Treats Peach Ashpond Chapter 3 Fashion on Campus
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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; both teacher heads agree on what is shown here.
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".