Fostering Excellence in Obstetrical Surgery
Bibliographic record
Abstract
R Douglas Wilson Department of Obstetrics and Gynecology, Cumming School of Medicine University of Calgary, Calgary, Alberta, CanadaCorrespondence: R Douglas Wilson, Department of Obstetrics and Gynecology, Cumming School of Medicine University of Calgary, Alberta, Canada, Tel +1 403-470-7229, Email doug.wilson@ahs.caIntroduction: This obstetric surgery review is directed toward the common obstetrical surgeries (caesarean delivery, VBAC/TOLAC, operative vaginal delivery, placenta accreta spectrum) with evidence for quality and safety to allow for obstetrical outcome excellence.Materials and Methods: This focused scoping review has used a structured process for article identification and inclusion for each of the focused surgeries.Results: The review results provide an obstetrical surgery (OS) overview for caesarean delivery, vaginal birth after caesarean delivery and/or trial of labor after caesarean delivery, operative vaginal delivery, placenta accreta spectrum; considerations for quality and safety variance due to non-clinical human factors; quality improvement (QI) tools; OS QI implementation cohorts; implementation considering certain barriers and solutions.Conclusion: Administrative health care systems and obstetrical surgery care providers cannot afford, not to consider and implement, certain evidenced-based “bottom-up/top-down” processes for quality and safety, as the patients will demand the quality and the safety, but the lawyers should not have to enforce it.Keywords: obstetrical safety, obstetrical quality, obstetrical morbidity, caesarean delivery, vaginal birth after caesarean delivery, trial of labor after caesarean delivery, operative vaginal delivery, placenta accreta spectrum, implementation process
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".