Bibliographic record
Abstract
In the article titled Recharged, published on page 117, Issue 3, Volume 30 in Canadian Journal of Rural Medicine,[1] there was an error: the name of Dr. Sarah Giles, co-chair of Rural and Remote Medicine 2025 was written incorrectly as Dr. Sarah Lesperance on page 117, 1st column, 5th line of 1st paragraph. The correct name of the co-chair should be read as “Dr. Sarah Giles” Réénergisés Dans l’article intitulé Réénergisés, publié sur la page 118, numéro 3, volume 30 de la Revue canadienne de médecine rurale,[1] il y avait une erreur : le nom de la Dre Sarah Giles, coprésidente de Rural and Remote Medicine 2025 était écrit incorrectement comme étant Dre Sarah Lesperance à la page 118 première colonne, 7e ligne du premier paragraphe Le nom correct de la coprésidente doit être lu comme « Dr Sarah Giles »
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 | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.087 | 0.081 |
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".