Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To estimate the rate of peripartum hysterectomy over the last 8 years in Calgary, the primary indication for peripartum hysterectomy (defined as any hysterectomy performed within 24 hours of a delivery), and whether there was an increase in the rate of peripartum hysterectomy during that time. METHOD: Detailed chart review of all cases of peripartum hysterectomy, 1999-2006, including previous obstetric history, details of the index pregnancy, indications for peripartum hysterectomy, outcome of the hysterectomy, and infant morbidity. RESULTS: The overall rate of peripartum hysterectomy was 87 of 108,154 or 0.8 per 1,000 deliveries. The primary indications for hysterectomy were uterine atony (32 of 87, 37%) and suspected placenta accreta (29 of 87, 33%). After hysterectomy, 46 (53%) women were admitted to the intensive care unit. Women were discharged home after a mean 6-day length of stay. The rate of peripartum hysterectomy did not appear to increase over time. CONCLUSION: Our population-based study found that abnormal placentation is the main indication for peripartum hysterectomy. The most important step in prevention of major postpartum hemorrhage is recognizing and assessing women's risk, although even perfect management of hemorrhage cannot always prevent surgery.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it