Bibliographic record
Abstract
During normal human pregnancy, the fetus accumulates 30 g of calcium. To meet this fetal demand, major maternal adaptations in calcium metabolism take place. Most significant among these is doubling of intestinal calcium absorption during pregnancy associated with increased levels of 1,25-dihydroxyvitamin D3. In addition, there may be increased resorption of trabecular bone during pregnancy. This, however, is not associated with adverse long-term outcomes such as osteoporosis and fractures. Calcium is actively transported across the placenta by a complex and elaborate system of proteins, allowing the fetus to maintain calcium levels higher than the mother. The regulation of placental calcium transport is largely unknown. In mothers with sufficient intake of dietary calcium, these adaptations are considered adequate for the calcium needs of the mother and fetus and the need for supplemental calcium in these mothers is controversial. In mothers with a decreased intake of dietary calcium, calcium supplementation has been demonstrated to reduce the incidence of gestational hypertensive disease and preterm birth. Disorders of calcium metabolism during pregnancy such as hyper- and hypoparathroidism, may present diagnostic and management challenges due to the maternal adaptations in calcium metabolism. This chapter will review the calcium metabolism and adaptations that occur during pregnancy, followed by a discussion of pathological calcium states during 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.009 |
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".