The use of Blood Concentrations of Vitamins and their Respective Functional Indicators to Define Folate and Vitamin B <sub>12</sub> Status
Bibliographic record
Abstract
In recent years there has been growing interest in the vitamins folic acid and vitamin B12 because of the realization that the status of these vitamins in populations is less than adequate, and that such inadequacy may be linked to adverse public health outcomes. This concern has prompted the United States, Canada, and other countries to fortify grain products with folic acid, while additional countries are considering doing so in the near future. This presentation provides a new approach which relies on the combination of the concentrations in blood of vitamins and their respective functional indicators to establish cutoff points for assessing folate and vitamin B12 status in populations. The premise is based on the fact that the relationship between plasma vitamin concentrations and their respective functional indicators is inverse and biphasic, with a steep slope at low concentrations of the vitamin and a more moderate slope at higher plasma vitamin concentrations. We propose that the intersection of these two slopes be used as a guideline for assessing the status of these vitamins and the adequacy of fortification programs. The cutoff would be 10 nmol/L for serum folate and 340 nmol/L for red blood cell folate, based on lowest plasma homocysteine. For serum vitamin B12, the cutoff would be 150 pmol/L based on lowest methylmalonic acid and 300 pmol/L based on lowest homocysteine.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".