Bibliographic record
Abstract
OBJECTIVE: To review 10 years of experience in removal of Chinese intrauterine devices (IUD) attained by a single gynecologist practicing in Canada. METHODS: Office records from women who presented requesting IUD removal between January 1999 and December 2008 were reviewed. Specific data including the time of IUD insertion, the country where the IUD was inserted, menstrual and obstetric histories, success of the IUD removal in an office setting, and the type of IUD removed were recorded. RESULTS: Of 314 women using a Chinese IUD, 227 (72.3%) had successful removal of the device in an office setting. Most women (86.6%) fitted with a Chinese IUD had no thread seen outside the cervix. A total of 279 Chinese IUDs were removed (from both the office setting and operating room), consisting of 11 different types; the most common type was the stainless steel ring (63.4%). Difficult removal was associated with absence of a visible thread outside the cervix, postmenopausal status, and no previous vaginal birth. The type of IUD and duration of placement did not affect the ease of removal. CONCLUSION: Knowledge about the different types of Chinese IUDs in use will enable gynecologists to provide optimal care to their patients.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".