Bibliographic record
Abstract
The Canadian Society of Plastic Surgeons (CSPS) is proud to officially announce its acquisition of the Canadian Journal of Plastic Surgery from Pulsus Group. This Journal has and will continue to promote idea exchange and continuous education for all of our members. Thanks to the initiative led by Dr Donald Lalonde, the CSPS board of directors approved in June 2011 a contract with Pulsus framed to respect previous agreements, and gradually transfer publication costs and income. The Society thanks Dr Peter Wyshnyski and Dr John Taylor for their relentless belief and support of the Journal, as they continue their legacy as editors emeritus. We congratulate Dr Edward Buchel, Dr Daniel Peters and Dr Douglas Mackay in their new active editorial roles under the wing of Dr Lalonde as the Journal chair. The breadth and reach of the Canadian Journal of Plastic Surgery is sure to grow with their master plan of increasing four-fold the editorial content reviewed by a pool of more than 40 world plastic surgery experts, and the incorporation of academic training and continuing medical education platforms, as well as sections devoted to feature topics and others targeting the financial aspects of practice. The transition to an online submission system will favour a more efficient and extensive transfer of information from the submission to the distribution process, and a more versatile one, allowing for the incorporation of various media including videos. With the engagement of the membership of the CSPS, and this new team’s master plan, the future is bright and exciting for the Canadian Journal of Plastic Surgery as it becomes a stronger voice of plastic surgery in Canada and abroad.
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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.321 | 0.312 |
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".