Feature Story: All’s well that ends well
Bibliographic record
Abstract
As she thought about it on Monday, October 12, Patience Umereweneza had plenty to be thankful for on this Thanksgiving Day. For one thing, she was less than a week away from graduating from the University of Regina with a Bachelor’s degree in health sciences. But what really made her Thanksgiving memorable was that it marked her father’s first visit to Canada since Patience arrived in Regina as a refugee in 2008. Long after turkey leftovers had been stored away in most Regina refrigerators, Samuel Umereweneza’s flight arrived from Thailand and father and daughter were reunited. “I feel like I won the lottery,” says Patience of her father’s unlikely arrival. “I was contemplating not going to Convocation. It would have been a very bittersweet moment to be on the stage without my father there. I wasn’t expecting that he would be able to come.” Only a few weeks ago, Patience could never have dreamed that her father would be in the Convocation audience, because his bid for a visitor’s visa was denied by Canadian embassy officials in Bangkok.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.110 | 0.030 |
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".