Near‐infrared spectroscopy characterizes vitamin deficiencies and infection status during pregnancy (804.1)
Bibliographic record
Abstract
Background: Near‐infrared (NIR) spectroscopy can identify spectral changes resulting from viral infections but has not been used to examine vitamin deficiencies or infection status during pregnancy. Objectives: To determine if vitamin status (sufficient/deficient) for A, D, B12, and folate, and presence/absence of respiratory, skin, oral, urogenital infections were reflected in NIR of maternal serum in 2nd (n=90) and 3rd trimester (n=100) in rural Panama. Methods: Eight functional groups (1600‐2400nm) were selected (CH, SH, POH, ROH, amide, amine, lactate and glucose). Values for each functional group and their ratios were compared by trimester between mothers with/without each deficiency, and with/without each infection using Mann‐Whitney U‐test. Results: Serum profiles differed by vitamin status in the 2nd trimester for vitamins A (amide:lactate, amine:lactate, lactate:glucose), B12 (POH:amide, ROH:amide) and folate (CH:ROH, SH:ROH). Differences were also observed for oral (CH:SH) and respiratory (amine:glucose) infections. In the third trimester, differences with vitamin D status involved both glucose and amine whereas folic acid deficiency involved differences only in amine. Only lactate differed between women with and without respiratory infections. Conclusion: NIR spectroscopy identified spectral differences due to nutrient deficiencies and infections. Grant Funding Source : SENACYT, NSERC
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".