Revolutionizing Women’s health: the quest for materials for next-generation, non-hormonal intrauterine devices
Bibliographic record
Abstract
Abstract With over 200 million users worldwide, copper intrauterine devices (Cu-IUDs) are the world’s most popular, non-hormonal, long-acting, and reversible contraception method. Cu-IUDs cause uncomfortable side effects such as longer and heavier menstruation and cramping, all of which persist for the duration of use and often lead to early removal. With the rise in concern about potential physical and psychological side effects from hormonal contraceptive use, an improvement in non-hormonal contraceptive options is needed to alleviate discomforting side effects and inhibit costs. This perspective article provides an overview of the current state of non-hormonal IUDs and experimental factors to consider when developing new materials that have potential as alternative contraceptives, including copper alloys, zinc, iron, and passive metals. It also explores the sustainability and socioeconomic impact of advancing non-hormonal contraceptive options and considers international policy, cultural factors, and costs that must be considered when developing these options. Overall, the article highlights the interdisciplinary nature of this field, the complexities involved in creating effective non-hormonal contraceptives, and the need for innovation and equity in contraceptive care.
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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 | 0.002 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".