Bibliographic record
Abstract
Editors of medical journals are accustomed to receiving feedback, both positive and negative, regarding the journals for which they are responsible. In talking to editors of other surgical and medical journals, the commonest problem they and authors face is the time it takes to have an article submitted, reviewed, accepted for publication and published. Obviously long delays in publication lead to author frustration and perhaps, on occasion, they will decide not to submit further work to the journal in question because of the issues around time to publication. At the Canadian Journal of Surgery we have been working diligently to try to improve the situation for both our authors and readers; obviously if published material is outdated it will be of minimal or no interest to our readers. To improve the turnaround time for submitted manuscripts and, we hope, the quality of the product for our readers we will be instituting some changes in the review process. We will begin this by canvassing our current list of reviewers to establish their continued interest in this often time-consuming task. We also intend to add new reviewers to our list and drop those who, for a variety of reasons, no longer wish to participate in the review process. We plan to institute a program that will ensure reviewers are not overloaded and we will try to keep an even balance of work amongst our reviewers. In order to ensure timely reviews, we are going to shorten the time line available for the reviewer to complete the task by instituting an automatic reminder process to expedite the timely return of the review. Articles that are not reviewed within the allocated time will promptly be sent to another reviewer so that the amount of time the article spends out of our office and in the hands of the reviewer(s) is minimized. We are also hoping to move at least part of the review process online as another step in speeding up this procedure; this will depend to some extent on the format in which the manuscript is submitted and the ability of the reviewer to receive and transmit such material online. To free up more editorial pages for manuscript publication we will also be changing significantly the format of Case Reports or Brief Communications. The new format will consist of a greatly abbreviated case report, with a limited number of illustrations and references. We all recognize that case reports can play an important role in the education of practising surgeons, particularly relating to aspects of surgical technique, rare diagnoses or innovative treatment. However, too many case reports that are too long are not good for the Journal or the readership; therefore we have decided to modify the Case Report section. More on this later. We are also discussing the possibility of changing some other aspects of the Journal, improving the format, making it more readable and establishing a clearer definition between articles primarily directed to continuing medical education and peer- reviewed original work. These are challenging times for print journals, and the Editorial Board of the Canadian Journal of Surgery is working hard along with the professionals at Canadian Medical Association Publications to keep the Journal current, relevant and readable. Your comments and suggestions, as always, are very welcome. James P. Waddell, MD Coeditor
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 | 0.018 | 0.155 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.031 | 0.016 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.280 | 0.270 |
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".