Levels of organochlorines and lipids across pregnancy, delivery and postpartum periods in women from Northern Norway
Bibliographic record
Abstract
The objective of this study was to investigate changes in the levels of common organochlorines (OCs) and lipids in maternal serum during and after pregnancy. A subset of 50 pregnant women from the North Norwegian Mother-and-Child Study was included in this study. Blood samples were collected during the 2(nd) trimester and postpartum (Day 3 and 6 weeks) in different regions of Northern Norway, and were analyzed for the Arctic Monitoring and Assessment Programme (AMAP) suite of OC contaminants. During the gestational period, both lipids and wet-weight OC levels peaked at birth and were the lowest at 6 weeks postpartum. When the OC concentrations were lipid-adjusted, this peaking was no longer evident. Wet-weight concentrations of OCs appear to be driven by the physiological lipid profiles and are interpreted to constitute biomarkers of lipidemia. It is suggested that this observation may have implications for the biomonitoring of individuals at risk of Type 2 diabetes. Both age and parity were strong predictors for the OCs measured, but no consistent association with body mass index (BMI) was evident. Independent of lipid-adjustment, all compounds were positively and significantly correlated with each other (within and across the three collection time periods). The peaking of OCs during pregnancy suggests that the period spanning the last weeks of the 3(rd) trimester and the early postpartum days constitutes an optimum sampling window purely from the analytical perspective.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".