A comparison of American and Canadian RBC folate concentrations
Bibliographic record
Abstract
In North America, folic acid fortification and supplementation policies have improved folate status and reduced the incidence of poor birth outcomes. This research aimed to compare RBC folate (RBF) concentrations in two nationally representative surveys: the 2007–2008 US NHANES and the 2007–2009 Canadian Health Measures Survey (CHMS). RBF was assessed in participants aged 6 to 79 years and in a subset of women of childbearing age (WCBA). Two different folate assay methods were employed— microbiologic assay (NHANES) and Immulite 2000 immunoassay (CHMS)—necessitating the application of a conversion equation to adjust the CHMS RBF data. T‐tests were used to examine country differences. RBF concentrations ≥906 nmol/L (considered optimal for neural tube defect risk reduction) were explored with a multiple logistic regression model. Median Canadian RBF (adjusted) were lower than those of Americans (988 nmol/L and 1106 nmol/L, respectively), but unadjusted Canadian median RBF values were higher (1248 nmol/L). Canadian WCBA (adjusted RBF) were less likely than American WCBA to have RBF ≥906 nmol/L (OR 0.58; 95% CI 0.37, 0.92), though Canadian WCBA with unadjusted RBF values were more likely to achieve this cut‐off than American WCBA (OR 1.90; 95% CI 1.03, 3.49). Harmonization of folate measurement procedures in future surveillance efforts would support comparisons and inform policy directions. Grant Funding Source : Canadian Institutes for Health Research Fellowship (180375) to C.K.C and Operating Grant (218776) to M.S.T, D.L.O and C.K.C.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".