Iodine in Edible Seaweed, Its Absorption, Dietary Use, and Relation to Iodine Nutrition in Arctic People
Bibliographic record
Abstract
Dietary iodine is important to human health, and both low and high iodine intake levels increase the risk of disease. Seaweed is rich in iodine and it is a common component in both Asian and in Arctic cuisines. While the intake and impact are known for Asian people, data are lacking for Arctic people. We aimed to (1) measure iodine content of dietary seaweeds in Greenland, (2) estimate iodine absorption, and (3) assess the impact on iodine intake in Arctic people. A hunter in East Greenland donated household seaweed for (1) measurement of iodine content and (2) ingestion of 45 g by each of eight individuals with subsequent urine collections. (3) In Ammassalik, 96% of 50–69-year-old Inuit reported on the frequency of intake of seaweed and provided a spot urine sample for iodine measurement. Seaweed species provided were Chondrus crispus and Ascophyllum nodosum. (1) The iodine content was 47 and 102 mg/g, respectively. (2) An estimated 1.1 and 1.9 mg of the ingested 2.1 and 4.6 of iodine in seaweed were excreted in the urine within 2 days. (3) More than two in three Inuit reported some dietary use, and 41% (109 of 268) reported a weekly intake of dietary seaweed, which was associated with iodine excretion. In conclusion, the iodine content of edible seaweeds in the Arctic is very high and bioavailable. Dietary intake contributed to the recommended iodine intake level, but marked variation in iodine excretion calls for evaluation of the impact on thyroid function.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".