ELEMENTAL STATUS OF ADULT NON-INDIGENOUS POPULATION OF KHANTY-MANSI AUTONOMOUS REGION
Bibliographic record
Abstract
The aim of the work is to study the elemental status of adult non-indigenous residents of the Khanty-Mansi Autonomous Okrug. Methods. The elemental composition of the hair was examined in 1 211 adult non-indigenous inhabitants of the Khanty-Mansi Autonomous Okrug: 348 (28.7 %) men and 863 (71.3 %) women aged 18 to 60 years. In the hairs of all examined individuals, the concentration of 25 chemical elements was determined by a combination of ICP- AES and MS-ICP methods. The results obtained were compared with reference values for the corresponding age. Results. In both groups, most of the average values of the concentration of chemical elements in the hair were in the range of physiologically optimal values. Mn concentration exceeded the upper limit in men by 1.5 times and in women by 1.7 times, Mg in women by 1.4 times and Hg in men by 1.4 times. A quarter of men and a fifth of women had Ca deficiency; in 26.4 % of men and 23.7 % of women - I. Mg excess was detected in 38.8 % of men and almost half of women; Mn excess - in half of men and 63.6 % of women. A quarter of the population of Khanty-Mansi Autonomous Okrug has I deficiency; a quarter of men and more than 40 % of women have Se deficiency. Zn excess in the hair was detected in 44.3 % of men and 34.5 % of women, and Hg in a quarter of men and 10 % of women. Conclusions. The relatively favorable picture of the elemental status of Khanty-Mansi Autonomous Okrug residents indicates the absence of serious environmental problems and reflects the high level of consumption and, probably, the availability of high quality medical services. Among women of childbearing age, the need to reduce the nutritional load of Hg should be promoted in order to reduce the risk of negative effects on fetal development during pregnancy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".