Biomonitoring Equivalents for interpretation of urinary iodine
Bibliographic record
Abstract
Iodine is an essential nutrient whose deficiency or excess exposure can cause adverse health effects. The primary sources of iodine exposure in the general population are iodized salt, dairy products, bread and sea food. Urinary iodine concentrations (UIC) have been measured by Canadian Health Measures Survey (CHMS) and US National Health and Nutrition Examination Survey (NHANES). The Institute of Medicine (IOM), the US Agency for Toxic Substances and Disease Registry (ATSDR) and World Health Organization (WHO) have established exposure guidance values for nutrition (IOM Estimated Average Requirement (EAR), Recommended Dietary Allowance (RDA), WHO Recommended Nutrient Intake (RNI)) and toxicity (IOM Tolerable Upper Intake Level (UL); ATSDR Minimal Risk Level (MRL), WHO International Programme on Chemical Safety (IPCS) Tolerable Daily Intake (TDI)). Using a urinary excretion fraction of 0.9, Biomonitoring Equivalents (BE) for the EAR, RDA, UL and MRL were derived for adults (60, 100, 730 and 450 μg/L, respectively) and children (50, 80, 580 and 360 μg/L, respectively). The population median UIC values from NHANES and CHMS for adults (140–181, 122–126 μg/L, respectively) and children (232, 189 μg/L, respectively) were above the criteria for assessing iodine nutrition, indicating that US and Canadian populations are likely to have adequate population iodine nutrition. The median UIC from NHANES and CHMS do not exceed BE values derived from exposure guidance values for toxicity.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".