Pharmacotherapy and Pregnancy: Highlights from the Second International Conference for Individualized Pharmacotherapy in Pregnancy
Bibliographic record
Abstract
To address provider struggles to provide evidence-based, rational drug therapy to pregnant women, a second conference was convened to highlight the current research in the field. Speakers from academic centers and institutions spoke about: the unique physiology and pathology of pregnancy; pharmacokinetic changes in pregnancy; thyroid disorders in pregnancy; pharmacogenetics in pregnancy; the role of CYP2D6 in pregnancy; treating addiction in pregnancy; the power of teratology networks to inform clinical decisions; the use of anti-depressants in pregnancy; and how to utilize computer-based modeling to aid with individualized pharmacotherapy in pregnancy. The Conference highlighted several areas of collaboration with the current Obstetrics Pharmacology Research Units Network (OPRU) and hoped to stimulate further collaboration and knowledge in the area with the common goal to improve the ability to safely and effectively use individualized pharmacotherapy in pregnancy.
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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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.029 | 0.037 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".