Bibliographic record
Abstract
For the past several years, one of the long-term projects of the editorial team has been to have the Canadian Journal of Optometry (CJO) included in at least one of the major indexing services like PubMed. This would not only raise the profile of the CJO but also make it more attractive to optometric scholars who need to publish in peer-reviewed publications. In the last year or so, it became clear that our publisher was unable to support changes required by the indexing services to which we had applied. As a result, a call for proposals was launched last winter to find a new publisher. The final selection was made in late June. As it happened, we learned that our previous publisher abruptly ceased all operations in early July. Fortunately, the summer issue with a nominal publication date of June 1, 2025, was already in the mail and the online (official) version published before this happened. This issue marks the first with our new publisher, Keith Communications Inc. KCI was quick to offer to begin work immediately on this issue. The masthead on the table of contents page reflects the change. The result will be an improved CJO that we hope will be acceptable not only to indexing services but also to you, our readers. There is another change in the masthead to note. Dr. Benoit Tousignant has been the Academic Editor since 2018. He is taking on more duties at l’École d’optométrie in Montreal and left his position with CJO in June. I thank him for his contributions to the CJO and wish him all the best.
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 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.178 | 0.123 |
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".