UTILIZATION AND REGIONAL VARIATION OF BREAST RECONSTRUCTION IN CANADA
Bibliographic record
Abstract
Division of Plastic Surgery, Sunnybrook and Women's College Health Sciences Center, Toronto, Ontario, Canada Correspondence to Dr. Semple, Division of Plastic Surgery, M1-522, Sunnybrook and Women's College Health Sciences Center, 2075 Bayview Avenue, Toronto, Ontario, Canada M4N 3M5, [email protected] Correspondence and brief communications are welcomed and need not concern only what has been published this journal. We shall print items of interest to our readers, such as experimental, clinical, and philosophical observations; reports of work in progress; educational notes; and travel accounts relevant to plastic surgery. We reserve the right to edit communications to meet requirements of space and format. Any financial interest relevant to the content of the correspondence must be disclosed. Submission of a letter constitutes permission for the American Society of Plastic Surgeons and its licensees and assignees to publish it in the journal and in any other form or medium. The views, opinions, and conclusions expressed in the Letters to the Editor represent the personal opinions of the individual writers and not those of the publisher, the Editorial Board, or the sponsors of the journal. Any stated views, opinions, and conclusions do not reflect the policy of any of the sponsoring organizations or of the institutions with which the writer is affiliated, and the publisher, the Editorial Board, and the sponsoring organizations assume no responsibility for the content of such letters.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".